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中学校 技術・家庭科 技術分野における内容D情報に関する技術において,情報通信ネットワークについてプログラミングを通して学ぶことが求められている.そこで,Webサーバで用いられるCGIを作成してWebサービスを作るプログラミング教材を基に,電子掲示版の仕組みを利用するWebサイトの制作を中心に学習や授業の補助となる資料を拡充し,データベースを利用したサービスが提供できるようにした教材を開発した.教材については大学生に利用してもらい分かりやすさなどを調べた., Junior high students in Japan are expected to learn how the network works through writing a program in division D information technology of technology education class. Then we developed education materials for the class based on one using which students create web-services programming CGI used on webservers. We expanded the material in the part of building bulletin board system and enabled to build web servers which use databases. We asked university students to use the materials and build web-services to investigate in the usefulness of the materials.

Cancer is the leading cause of death worldwide, resulting in the mortality of more than 10 million people in 2020, according to Global Cancer Statistics 2020. A potential cancer therapy involves targeting the DNA repair process by inhibiting PARP-1. In this study, classification models were constructed using a non-redundant set of 2018 PARP-1 inhibitors. Briefly, compounds were described by 12 fingerprint types and built using the random forest algorithm concomitant with various sampling approaches. Results indicated that PubChem with an oversampling approach yielded the best performance, with a Matthews correlation coefficient > 0.7 while also affording interpretable molecular features. Moreover, feature importance, as determined from the Gini index, revealed that the aromatic/cyclic/heterocyclic moiety, nitrogen-containing fingerprints, and the ether/aldehyde/alcohol moiety were important for PARP-1 inhibition. Finally, our predictive model was deployed as a web application called PARP1pred and is publicly available at https://parp1pred.streamlitapp.com, allowing users to predict the biological activity of query compounds using their SMILES notation as the input. It is anticipated that the model described herein will aid in the discovery of effective PARP-1 inhibitors., EXCLI Journal; 22:Doc84; ISSN 1611-2156

Proportion of cancerous cells in a tumor sample, known as "tumor purity", is a major source of confounding factor in cancer data analyses. Lots of computational methods are available for estimating tumor purity from different types of genomics data or based on different platforms, which makes it difficult to compare and integrate the estimated results. To rectify the deviation caused by tumor purity effect, a number of methods for downstream data analysis have been developed, including tumor sample clustering, association study and differential methylation between tumor samples. However, using these computational tools remains a daunting task for many researchers since they require non-trivial computational skills. To this end, we present Purimeth, an integrated web-based tool for estimating and accounting for tumor purity in cancer DNA methylation studies. Purimeth implements three state-of-the-art methods for tumor purity estimation from DNA methylation array data: InfiniumPurify, MEpurity and PAMES. It also provides graphical interface for various analyses including differential methylation (DM), sample clustering, and purification of tumor methylomes, all with the consideration of tumor purities. In addition, Purimeth catalogs estimated tumor purities for TCGA samples from nine methods for users to visualize and explore. In conclusion, Purimeth provides an easy-operated way for researchers to explore tumor purity and implement cancer methylation data analysis. It is developed using Shiny (Version 1.6.0) and freely available at http://purimeth.comp-epi.com/.

The determination of core genes in viral and bacterial genomes is crucial for a better understanding of their relatedness and for their classification. CoreGenes5.0 is an updated user-friendly web-based software tool for the identification of core genes in and data mining of viral and bacterial genomes. This tool has been useful in the resolution of several issues arising in the taxonomic analysis of bacteriophages and has incorporated many suggestions from researchers in that community. The webserver displays result in a format that is easy to understand and allows for automated batch processing, without the need for any user-installed bioinformatics software. CoreGenes5.0 uses group protein clustering of genomes with one of three algorithm options to output a table of core genes from the input genomes. Previously annotated “unknown genes” may be identified with homologues in the output. The updated version of CoreGenes is able to handle more genomes, is faster, and is more robust, providing easier analysis of custom or proprietary datasets. CoreGenes5.0 is accessible at coregenes.org, migrating from a previous site.

The web servers (WSGI-Python) and (PHP-Apache) are in middleware tier architecture. Middleware architecture is between frontend tier and backend tier, otherwise it’s a connection between frontend tier and backend tier for three tier architecture. The ELearning systems are designed by two different dynamic web technologies. First is by Python-WSGI and the second is by Personal Home Page (PHP-Apache). The two websites were designed with different open source and cross platform web technologies programming language namely; Python and PHP in the same structure and weight will evaluate perform over two different operating systems (OSs): 1) Windows-16 and 2) Linux-Ubuntu 20.4. Both systems run over the same computer architecture (64bit) as a server side with a common backend MySQL web database for both of them. Nevertheless, the middleware for PHP is a cross Apache MySQL PHP Perl (XAMPP), but the middleware for Python is Pycharm and the web server gateway interface (WSGI). WSGI and Apache are both web servers and this paper will show which of them has a better response time (RT). On the one hand, the experimental results demonstrate that the Python-WSGI is even weightier in Mbyte than PHP-Apache, on the other hand Python is still faster and more accurate than PHP. The designed SPG is by handwriting codes: one time designed the SPG by PHP source code and the other time designed by Python source code. Both Python-WSGI and PHP-Apache results are targeted to compare by the least time in milliseconds and take in to account enhanced performance.

Artificial intelligence can train the related known drug data into deep learning models for drug design, while classical algorithms can design drugs through established and predefined procedures. Both deep learning and classical algorithms have their merits for drug design. Here, the webserver WADDAICA is built to employ the advantage of deep learning model and classical algorithms for drug design. The WADDAICA mainly contains two modules. In the first module, WADDAICA provides deep learning models for scaffold hopping of compounds to modify or design new novel drugs. The deep learning model which is used in WADDAICA shows a good scoring power based on the PDBbind database. In the second module, WADDAICA supplies functions for modifying or designing new novel drugs by classical algorithms. WADDAICA shows better Pearson and Spearman correlations of binding affinity than Autodock Vina that is considered to have the best scoring power. Besides, WADDAICA supplies a friendly and convenient web interface for users to submit drug design jobs. We believe that WADDAICA is a useful and effective tool to help researchers to modify or design novel drugs by deep learning models and classical algorithms. WADDAICA is free and accessible at https://bqflab.github.io or https://heisenberg.ucam.edu:5000.

The concept of chemical space is a cornerstone in chemoinformatics, and it has broad conceptual and practical applicability in many areas of chemistry, including drug design and discovery. One of the most considerable impacts is in the study of structure-property relationships where the property can be a biological activity or any other characteristic of interest to a particular chemistry discipline. The chemical space is highly dependent on the molecular representation that is also a cornerstone concept in computational chemistry. Herein, we discuss the recent progress on chemoinformatic tools developed to expand and characterize the chemical space of compound data sets using different types of molecular representations, generate visual representations of such spaces, and explore structure-property relationships in the context of chemical spaces. We emphasize the development of methods and freely available tools focusing on drug discovery applications. We also comment on the general advantages and shortcomings of using freely available and easy-to-use tools and discuss the value of using such open resources for research, education, and scientific dissemination.

Viruses with rapid replication and easy mutation can become resistant to antiviral drug treatment. With novel viral infections emerging, such as the recent COVID-19 pandemic, novel antiviral therapies are urgently needed. Antiviral proteins, such as interferon, have been used for treating chronic hepatitis C infections for decades. Natural-origin antimicrobial peptides, such as defensins, have also been identified as possessing antiviral activities, including direct antiviral effects and the ability to induce indirect immune responses to viruses. To promote the development of antiviral drugs, we constructed a data repository of antiviral peptides and proteins (DRAVP). The database provides general information, antiviral activity, structure information, physicochemical information, and literature information for peptides and proteins. Because most of the proteins and peptides lack experimentally determined structures, AlphaFold was used to predict each antiviral peptide’s structure. A free website for users (http://dravp.cpu-bioinfor.org/, accessed on 30 August 2022) was constructed to facilitate data retrieval and sequence analysis. Additionally, all the data can be accessed from the web interface. The DRAVP database aims to be a useful resource for developing antiviral drugs.

The LAHMA web server for structural analysis of homologous proteins is presented., Comparison of homologous structure models is a key step in analyzing protein structure. With a wealth of homologous structures, comparison becomes a tedious process, and often only a small (user-biased) selection of data is used. A multitude of structural superposition algorithms are then typically used to visualize the structures together in 3D and to compare them. Here, the Local Annotation of Homology-Matched Amino acids (LAHMA) website (https://lahma.pdb-redo.eu) is presented, which compares any structure model with all of its close homologs from the PDB-REDO databank. LAHMA displays structural features in sequence space, allowing users to uncover differences between homologous structure models that can be analyzed for their relevance to chemistry or biology. LAHMA visualizes numerous structural features, also allowing one-click comparison of structure-quality plots (for example the Ramachandran plot) and ‘in-browser’ structural visualization of 3D models.

Background Protein–peptide interactions play a fundamental role in a wide variety of biological processes, such as cell signaling, regulatory networks, immune responses, and enzyme inhibition. Peptides are characterized by low toxicity and small interface areas; therefore, they are good targets for therapeutic strategies, rational drug planning and protein inhibition. Approximately 10% of the ethical pharmaceutical market is protein/peptide-based. Furthermore, it is estimated that 40% of protein interactions are mediated by peptides. Despite the fast increase in the volume of biological data, particularly on sequences and structures, there remains a lack of broad and comprehensive protein–peptide databases and tools that allow the retrieval, characterization and understanding of protein–peptide recognition and consequently support peptide design. Results We introduce Propedia, a comprehensive and up-to-date database with a web interface that permits clustering, searching and visualizing of protein–peptide complexes according to varied criteria. Propedia comprises over 19,000 high-resolution structures from the Protein Data Bank including structural and sequence information from protein–peptide complexes. The main advantage of Propedia over other peptide databases is that it allows a more comprehensive analysis of similarity and redundancy. It was constructed based on a hybrid clustering algorithm that compares and groups peptides by sequences, interface structures and binding sites. Propedia is available through a graphical, user-friendly and functional interface where users can retrieve, and analyze complexes and download each search data set. We performed case studies and verified that the utility of Propedia scores to rank promissing interacting peptides. In a study involving predicting peptides to inhibit SARS-CoV-2 main protease, we showed that Propedia scores related to similarity between different peptide complexes with SARS-CoV-2 main protease are in agreement with molecular dynamics free energy calculation. Conclusions Propedia is a database and tool to support structure-based rational design of peptides for special purposes. Protein–peptide interactions can be useful to predict, classifying and scoring complexes or for designing new molecules as well. Propedia is up-to-date as a ready-to-use webserver with a friendly and resourceful interface and is available at: https://bioinfo.dcc.ufmg.br/propedia

A recent advance in the disorder prediction field is the development of the quality assessment (QA) scores. QA scores complement the propensities produced by the disorder predictors by identifying regions where these predictions are more likely to be correct. We develop, empirically test and release a new QA tool, QUARTERplus, that addresses several key drawbacks of the current QA method, QUARTER. QUARTERplus is the first solution that utilizes QA scores and the associated input disorder predictions to produce very accurate disorder predictions with the help of a modern deep learning meta-model. The deep neural network utilizes the QA scores to identify and fix the regions where the original/input disorder predictions are poor. More importantly, the accurate QUATERplus’s predictions are accompanied by easy to interpret residue-level QA scores that reliably quantify their residue-level predictive quality. We provide these interpretable QA scores for QUARTERplus and 10 other popular disorder predictors. Empirical tests on a large and independent (low similarity) test dataset show that QUARTERplus predictions secure AUC = 0.93 and are statistically more accurate than the results of twelve state-of-the-art disorder predictors. We also demonstrate that the new QA scores produced by QUARTERplus are highly correlated with the actual predictive quality and that they can be effectively used to identify regions of correct disorder predictions. This feature empowers the users to easily identify which parts of the predictions generated by the modern disorder predictors are more trustworthy. QUARTERplus is available as a convenient webserver at http://biomine.cs.vcu.edu/servers/QUARTERplus/ .

Motivation Poor protein solubility hinders the production of many therapeutic and industrially useful proteins. Experimental efforts to increase solubility are plagued by low success rates and often reduce biological activity. Computational prediction of protein expressibility and solubility in Escherichia coli using only sequence information could reduce the cost of experimental studies by enabling prioritization of highly soluble proteins. Results A new tool for sequence-based prediction of soluble protein expression in E.coli, SoluProt, was created using the gradient boosting machine technique with the TargetTrack database as a training set. When evaluated against a balanced independent test set derived from the NESG database, SoluProt’s accuracy of 58.5% and AUC of 0.62 exceeded those of a suite of alternative solubility prediction tools. There is also evidence that it could significantly increase the success rate of experimental protein studies. SoluProt is freely available as a standalone program and a user-friendly webserver at https://loschmidt.chemi.muni.cz/soluprot/. Availability and implementation https://loschmidt.chemi.muni.cz/soluprot/. Supplementary information Supplementary data are available at Bioinformatics online.

Target‐site mutations and detoxification gene overexpression are two major mechanisms conferring insecticide resistance. Molecular assays applied to detect these resistance genetic markers are time‐consuming and with high false‐positive rates. RNA‐Seq data contains information on the variations within expressed genomic regions and expression of detoxification genes. However, there is no corresponding method to detect resistance markers at present. Here, we collected 66 reported resistance mutations of four insecticide targets (AChE, VGSC, RyR, and nAChR) from 82 insect species. Next, we obtained 403 sequences of the four target genes and 12,665 sequences of three kinds of detoxification genes including P450s, GSTs, and CCEs. Then, we developed a Perl program, FastD, to detect target‐site mutations and overexpressed detoxification genes from RNA‐Seq data and constructed a web server for FastD (http://www.insect-genome.com/fastd). The estimation of FastD on simulated RNA‐Seq data showed high sensitivity and specificity. We applied FastD to detect resistant markers in 15 populations of six insects, Plutella xylostella, Aphis gossypii, Anopheles arabiensis, Musca domestica, Leptinotarsa decemlineata and Apis mellifera. Results showed that 11 RyR mutations in P. xylostella, one nAChR mutation in A. gossypii, one VGSC mutation in A. arabiensis and five VGSC mutations in M. domestica were found to be with frequency difference >40% between resistant and susceptible populations including previously confirmed mutations G4946E in RyR, R81T in nAChR and L1014F in VGSC. And 49 detoxification genes were found to be overexpressed in resistant populations compared with susceptible populations including previously confirmed detoxification genes CYP6BG1, CYP6CY22, CYP6CY13, CYP6P3, CYP6M2, CYP6P4 and CYP4G16. The candidate target‐site mutations and detoxification genes were worth further validation. Resistance estimates according to confirmed markers were consistent with population phenotypes, confirming the reliability of this program in predicting population resistance at omics‐level., We developed a program called FastD to detect the insecticide target‐site mutations and overexpressed detoxification genes from RNA‐Seq data and constructed a corresponding web server for FastD (http://www.insect-genome.com/fastd) in this article.

[ES] Con este trabajo final de grado se pretende diseñar e implementar un sistema autogestionable para un estudio de arquitectura. El sistema consistirá en tres aplicaciones web. Las dos primeras, con diseños diferentes, servirán para presentar los proyectos de arquitectura, con imágenes de los planos, información de sus características, información del despacho de arquitectura y la posibilidad de contactar vía un formulario. La tercera aplicación web será un panel de administrador que sólo podrá ser accedido por los dueños del despacho y será utilizado para crear, modificar y borrar los proyectos mostrados en las páginas mencionadas anteriormente. Desde el panel de administrador se podrán subir fotos y planos de las construcciones, describir las características de los proyectos arquitectónicos, cambiar el orden de visualización de los proyectos en las páginas y consultar las peticiones enviadas a través de los formularios de cliente., [CA] Amb aquest treball final de grau es pretén dissenyar i implementar un sistema autogestionable per a un estudi d’arquitectura. El sistema consistirà en tres aplicacions web. Les dues primeres, amb dissenys diferents, serviran per presentar els projectes d’arquitectura, amb imatges dels plànols, informació de les seves característiques, informació de l’despatx d’arquitectura i la possibilitat de contactar via un formulari. La tercera aplicació web serà un panell d’administrador que només podrà ser accedit pels propietaris de l’- despatx, i serà utilitzat per a crear, modificar, esborrar els projectes mostrats a les pàgines esmentades anteriorment. Des del panell d’administrador es podran pujar fotos i plànols de les construccions, descriure les característiques dels projectes arquitectònics, canviar l’ordre de visualització dels projectes a les pàgines i consultar les peticions enviades a través dels formularis de client., [EN] With this final degree project we intended to implement a self-manageable system for an architecture studio. The system will consist of three web applications. The first two, with different designs, will serve the purpose of listing architecture projects (with images of house projects, their information and characteristics). The websites will also contain information on the architecture office and the possibility of contacting through a web form. The third web application will be an administrator panel that can only be accessed by the owners of the studio, and will be used to create, modify, delete the projects shown in the previously mentioned web sites. From the administrator panel it will be possible to upload photos and plans of the buildings, describe the characteristics of the architectural projects, change the order in which the projects are displayed on the web sites and consult the questions sent through the customer web forms.

Protein phosphorylation is an important type of post-translational modification that regulates various activities of cell life inside human body. The accurate identification of phosphorylation sites can provide new insights for revealing the specific function of protein. However, it is time-consuming and inefficient to apply the experiment-based techniques in investigating the phosphorylation sites in proteins. Additionally, computational approaches are regarded as an ideal choice in such a big data era. Therefore, in this work, we designed a new computational method to identify phosphorylation sites. At first, phosphorylation data was collected from human proteins to construct an objective and strict benchmark dataset. By a series of feature analysis, we found that the distributions of conservation scores and nine physicochemical properties surrounding the phosphorylation sites in positive samples are significantly different from those surrounding non-phosphorylation sites in negative samples. Based on these features, a novel sequence-based method for predicting the phosphorylation sites in human proteomics was proposed, which incorporated the conservation scores with position-associated attributes that reflect the correlation of physicochemical characteristics among amino acid residues. Furthermore, the analysis of variance (ANOVA) was utilized to obtain the optimal feature subset which could produce the highest accuracy. Comparison with the published predictor demonstrated the superiority of our predictor. Finally, a user-friendly online tool called iPhoPred was established and can be freely available at http://lin-group.cn/server/iPhoPred/ . We hope the tool will provide important guide for the study of protein phosphorylation.

Accurate prediction of lymph-node metastasis in cancers is pivotal for the next targeted clinical interventions that allow favorable prognosis for patients. Different molecular profiles (mRNA and non-coding RNAs) have been widely used to establish classifiers for cancer prediction (e.g., tumor origin, cancerous or non-cancerous state, cancer subtype). However, few studies focus on lymphatic metastasis evaluation using these profiles, and the performance of classifiers based on different profiles has also not been compared. Here, differentially expressed mRNAs, miRNAs, and lncRNAs between lymph-node metastatic and non-metastatic groups were identified as molecular signatures to construct classifiers for lymphatic metastasis prediction in different cancers. With this similar feature selection strategy, support vector machine (SVM) classifiers based on different profiles were systematically compared in their prediction performance. For representative cancers (a total of nine types), these classifiers achieved comparative overall accuracies of 81.00% (67.96–92.19%), 81.97% (70.83–95.24%), and 80.78% (69.61–90.00%) on independent mRNA, miRNA, and lncRNA datasets, with a small set of biomarkers (6, 12, and 4 on average). Therefore, our proposed feature selection strategies are economical and efficient to identify biomarkers that aid in developing competitive classifiers for predicting lymph-node metastasis in cancers. A user-friendly webserver was also deployed to help researchers in metastasis risk determination by submitting their expression profiles of different origins.

[ES] El presente trabajo describe el método para implementar una plataforma virtual que permita crear un Digital Twin de una celda automatizada con dos robots colaborativos que intercambian una pieza empleando visión artificial. La plataforma es completamente gratuita y permite a futuros alumnos e interesados entrenarse o desarrollar proyectos de investigación rompiendo las barreras de acceso a estas tecnologías involucradas en la Industria 4.0. El Digital Twin habilita la migración de todos los programas implementados a los dispositivos físicos en cualquier instante tras la depuración de posibles colisiones y errores en el código. Para materializar los módulos, se utilizan simuladores de programación fuera de línea como RoboDK, para la representación gráfica del proceso y la secuencia de trabajo, URSim como modelo fisicomatemático de los robot UR3e, CODESYS permite emular un softPLC con la lógica de control, este componente además tiene embebido un WebServer para representar todos los datos y el control de la celda, el cuál presenta un concepto de diseño gráfico desarrollado desde los cimientos del proyecto por el autor, al mismo tiempo y con el mismo propósito, una pantalla HMI de Omron actúa como interfaz hombre-máquina. La visión artificial se programa empleando lenguaje Python, el cual aprovecha las APIs de RoboDK para simular una cámara 2D. Todos los elementos se interrelacionan entre sí en tiempo real y se comunican con dos servicios de cloud computing, comenzando por UBIDOTS para monitorizar parámetros de la celda y establecer la posición en la cual el primer robot entrega la pieza en el proceso de intercambio a través de variables que se manipulan por medio de protocolos como OPC UA, MQTT, JSON y nodos implementados en Node-Red, la segunda plataforma está desarrollada por CODESYS Automation Server, un servicio web donde el usuario puede consultar el estado del controlador, distintas versiones del código entre las cuales se puede elegir cual ejecutar, o programar directamente el autómata desde un navegador web rompiendo la barrera de la programación anclada a un PC convencional, pudiendo realizar dicha tarea en una Tablet o un Smartphone en cualquier punto geográfico., [EN] This project describes the method to implement a virtual platform to create a Digital Twin of an automated cell with two collaborative robots exchanging a part using artificial vision. The platform is completely free of charge and allows future students and interested parties to train or develop research projects by breaking down the barriers of access to these technologies involved in Industry 4.0. The Digital Twin enables the migration of all implemented programs to the physical devices at any time after debugging possible collisions and errors in the code. To realise the modules, offline programming simulators such as RoboDK are used for the graphical representation of the process and the work sequence, URSim as a physicomathematical model of the UR3e robots, CODESYS allows the emulation of a softPLC with the control logic, this component also has an embedded WebServer to represent all the data and control of the cell, which presents a graphic design concept developed from the foundations of the project by the author, at the same time and for the same purpose, an Omron HMI screen acts as a human-machine interface. The machine vision is programmed using Python language, which takes advantage of the RoboDK APIs to simulate a 2D camera. All the elements interrelate with each other in real time and communicate with two cloud computing services, starting with UBIDOTS to monitor cell parameters and establish the position in which the first robot delivers the part in the exchange process through variables that are manipulated by means of protocols such as OPC UA, MQTT, JSON and nodes implemented in Node-Red, the second platform is developed by CODESYS Automation Server, a web service where the user can check the status of the controller, different versions of the code from which you can choose which one to run, or program the automaton directly from a web browser, breaking the barrier of programming anchored to a conventional PC, being able to perform this task on a Tablet or Smartphone at any geographical location.

Die vorliegende Bachelorarbeit hat als Ziel, die Aktorik sowie Sensorik des Testsystems für das automatisierte Fahren an einem Modellfahrzeug im Maßstab 1:5 zu testen und mit einfachen Fahrassistenzsystemen zu erweitern. Für dieses Ziel wurde im ersten Abschnitt dieses neue Testsystem analysiert und in das Thema Fahrerassistenzsysteme eingearbeitet. Die am Fahrzeug verbaute Aktorik sowie Sensorik wurde im nächsten Schritt in Betrieb genommen, getestet und die Daten der Sensoren ausgewertet.Auf Basis dieser Daten wurde ein Webserver für die Live-Beobachtung der Sensordaten während der Testfahrten entwickelt. Dieser Webserver wurde mit einer Startseite, Seiten für die einzelnen verbauten Sensoren und den entwickelten Fahrerassistenzsystemen ausgestattet. Durch die Beobachtung der Sensordaten in Echtzeit wurde die Entwicklung und Inbetriebnahme der Fahrerassistenzsysteme erleichtert. In dieser Arbeit wurden dem Testsystem die Fahrerassistenzsysteme Parkassistent und Geschwindigkeitsregelanlage implementiert. Nach der erfolgreichen Überprüfung dieser Assistenzsysteme ist das Testsystem bereit für weitere Erweiterungen im Bereich Fahrerassistenzsysteme und autonomes Fahren. The aim of this bachelor thesis was to test the actuators and sensors of the test system for automated driving on a model vehicle on a scale of 1:5 and to expand it with simple driver assistance systems. For this goal, this new test system was analysed in the first section and incorporated into the topic of driver assistance systems. In the next step, the actuators and sensors installed on the vehicle were put into operation, tested and the data from the sensors evaluated.Based on this data, a web server was developed for live observation of the sensor data during the test drives. This web server was equipped with a start page, pages for the individual sensors installed and the driver assistance systems developed. The real-time sensor data observation facilitated the development and commissioning of the driver assistance systems. In this work, the driver assistance systems parking assistant and cruise control were implemented into the test system. After the successful testing of these assistance systems, the test system is ready for further extensions in the field of driver assistance systems and autonomous driving. Christian Götschl Abweichender Titel laut Übersetzung der Verfasserin/des Verfassers Bachelorarbeit FH JOANNEUM 2021

Globally fermented foods are in demands due to their functional and nutritional benefits. These foods are sources of probiotic organisms and bioactive peptides, various amino acids, enzymes etc. that provides numerous health benefits. FermFooDb (https://webs.iiitd.edu.in/raghava/fermfoodb/) is a manually curated database of bioactive peptides derived from wide range of foods that maintain comprehensive information about peptides and process of fermentation. This database comprises of 2205 entries with following major fields, peptide sequence, Mass and IC50, food source, functional activity, fermentation conditions, starter culture, testing conditions of sequences in vitro or in vivo, type of model and method of analysis. The bioactive peptides in our database have wide range of therapeutic potentials that includes antihypertensive, ACE-inhibitory, antioxidant, antimicrobial, immunomodulatory and cholesterol lowering peptides. These bioactive peptides were derived from different types of fermented foods that include milk, cheese, yogurt, wheat and rice. Numerous, web-based tools have been integrated to retrieve data, peptide mapping of proteins, similarity search and multiple-sequence alignment. This database will be useful for the food industry and researchers to explore full therapeutic potential of fermented foods from specific cultures., Bioactive peptide, Database, Webserver, Microbial fermentation, Functional food.

Evidence that Hepatitis D virus (HDV) genotype is involved in HDV infection pathogenesis is increasing. Indeed, HDV genotypes have been shown to be linked to different outcomes in terms of liver fibrosis and treatment response. Herein, we show that the promising HDVdb genotyping tool available online can lead to wrong genotyping results. The current HDVdb algorithm should be carefully considered as a “beta-version” and warrants algorithm core corrections, as soon as possible, for an optimal and beneficial use.

Hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations help predict ligand poses in human G protein-coupled receptors (hGPCRs), the most important protein superfamily for pharmacological applications. This approach allows the description of the ligand, the binding cavity, and the surrounding water molecules at atomistic resolution, while coarse-graining the rest of the receptor. Here, we present the Hybrid MM/CG Webserver (mmcg.grs.kfa-juelich.de) that automatizes and speeds up the MM/CG simulation setup of hGPCR/ligand complexes. Initial structures for such complexes can be easily and efficiently generated with other webservers. The Hybrid MM/CG server also allows for equilibration of the systems, either fully automatically or interactively. The results are visualized online (using both interactive 3D visualizations and analysis plots), helping the user identify possible issues and modify the setup parameters accordingly. Furthermore, the prepared system can be downloaded and the simulation continued locally.

Das Wachstum von Bakterien ist ein komplexes, aber gut organisiertes Spiel, bei dem ausreichende Mengen verschiedener Zellkomponenten produziert werden müssen, um Zellteilungen durchzuführen und den Zyklus zu wiederholen. Dabei kann vieles schief gehen - deshalb haben sich bei Bakterien mehrere Strategien entwickelt, um sicherzustellen, dass alle Prozesse synchronisiert ablaufen. Diese Problematik wird zusätzlich erschwert, da die Zellen ihre Wachstumsrate an ihre Lebensbedingungen anpassen, was wiederum die gesamte Zellphysiologie beeinflusst. Eine bemerkenswerte Änderung ist, dass mit zunehmender Nährstoffverfügbarkeit und -qualität die durchschnittliche Größe der Zellen und die Konzentration der Ribosomen in der Zelle steigt; letztere ermöglicht sowohl die Produktion der größten Makromolekülfraktion in der Zelle (Proteine) als auch mehr Ribosomen, die für ein schnelles Wachstum erforderlich ist. Mit der Zunahme des Volumens der Zelle kommt eine erforderliche Vergrößerung der Oberfläche, da ein Ungleichgewicht zwischen diesen beiden zu einem unhaltbaren Innendruck führen würde. Wie stellen Bakterien dann sicher, dass das Volumenwachstum mit der Produktion von Zellhüllenkomponenten synchronisiert wird, so dass die Zellhomöostase erhalten bleibt, insbesondere bei schwankender Wachstumsrate? Genomischer Kontext ist bekannt dafür die Koregulation von Genen zu unterstützen und dadurch ihre Expression auf verschiedene zelluläre Reize zu synchronisieren. Da das bakterielle Genom sehr unbeständig ist, deutet die Existenz konservierter genomischer Kontexte auf wichtige Ansatzpunkte der Koregulation hin. Könnte es sein, dass in diesen Genclustern das fehlende Puzzlestück zur Erklärung der Synchronisierung von Volumenwachstum und Oberflächenexpansion liegt? Um diese Frage zu beantworten, werden in dieser Arbeit drei Fragestellungen bearbeitet. Zunächst entwickeln wir ein Genomvergleichstool (www.GenCoDB.org), dass die ständig wachsende Verfügbarkeit von sequenzierten bakteriellen Genomen nutzt, um die Analyse, den Vergleich und die Quantifizierung von Genomkontexten zu erleichtern. Dies beruht auf neuartigen Strategien, um die Breite der Genomdaten, die auf rechnerisch effiziente Weise verfügbar sind, zu berücksichtigen, die Wirkung von Probenahmeverzerrungen, die sich in den meisten bakteriellen Datensätzen finden lassen, zu verringern und sicherzustellen, dass Kandidaten für ihren evolutionären Kontext als signifikant angesehen werden können. Die Verfügbarkeit von GenCoDB wird die genomische Kontextforschung in der Mikrobiologiegemeinschaft erleichtern und den Zugang von Nicht-Bioinformatikern zu dieser Quelle wichtiger biologischer Daten verbessern. Mit unseren neuen Erkenntnissen zu genomischen Nachbarschaftsdaten untersuchen wir anschließend die Evolution konservierter Gencluster und versuchen mögliche Kandidaten zur Regulation der Volumen-Oberfläche zu identifizieren. Beim Nachvollziehen der Verwandschaftsverhältnisse von Genclustern im gesamten Bakterienreich stellen wir fest, dass die Co-Orientierung stark konserviert ist, was jedoch weder den späteren Kontext um das Cluster herum noch die Expansion des Clusters beeinflusst. Wir finden heraus, dass die vertikale Übertragung und nicht der horizontale Gentransfer der treibende Faktor für das Auftreten von Genclustern in Chromosomen ist und dass Cluster an Origin und Terminator mit größerer Wahrscheinlichkeit instand gehalten werden. Schließlich stellen wir fest, dass trotz der scheinbaren Häufigkeit der Operon-Organisation in Genclustern, diese eher aufgrund anderer selektiver Belastungen wie Protein-Protein-Interaktionen innerhalb des Clusters und des essentiellen Statuses ihrer Gene aufrechterhalten werden, und dass Operons ein Produkt der Co-Lokalisierung über die evolutionäre Zeit zu sein scheinen. Wir identifizieren einen einzelnen Gencluster-Kandidaten, der allen Anforderungen gerrecht wird, die unserer Meinung nach für die Homöostase des Zellwachstums der Oberflächenexpansion erforderlich sind. Die Anforderungen sind eine hohe Verbreitung innerhalb von Bakterien sowie eine Verbindung zwischen ribosomenassoziierten Proteinen (Wachstum) und Zellhüllesynthese. In Übereinstimmung mit unseren Evolutionsstudien finden wir heraus, dass das Cluster zwar ko-reguliert ist, dies aber nicht der selektive Druck zu sein scheint, der diese verschiedenen Prozesse zusammenführte. Stattdessen finden wir eine potenzielle Rolle des genomischen Channellings, das die Produktion von Pyrimidinen mit der Synthese der Zellhülle verknüpft, die von der Co-Lokalisierung dieses Clusters abhängig ist. Insgesamt wird diese Arbeit das Verständnis der Chromosomenentwicklung in Bakterien und die potenziellen Auswirkungen des genomischen Kontextes auf die Metabolitenverwertung erweitern. Es stellt die Rolle von Operons und horizontalem Gentransfer bei der langfristigen Entwicklung der Genordnung in Frage und bietet eine neue quantitative und statistische Ressource, die den Zugang zu über 1,9 Millionen Gen-Nachbarschaften ermöglicht., The growth of bacteria is a complex but well-orchestrated dance involving the repetitive and reproducible production of their diverse cellular components in order to divide. A lot can go astray and therefore the cell has developed several strategies in order to ensure everything remains synchronized. This problem is only further complicated as the cells adjust their growth rate to their living conditions resulting in ripple effects throughout the cell physiology. One notable change is that as nutrient availability and quality increases so too does the average size and the concentration of ribosomes in the cell. The latter enables the production of the largest macromolecule faction in the cell (proteins) including the production of more ribosomes required to maintain the protein synthesis requirements. With the increase in volume of the cell comes a required increase in surface area, and a disbalance between these two would result in untenable levels of internal pressure. How then do bacteria ensure that volume growth is synchronized with the production of cell envelope components so that cell homeostasis is maintained, especially in the face of fluctuating growth rate? Genomic context is known to assist in co-regulation of genes thereby synchronizing them to respond to different cellular stimuli. As the bacterial genome is highly fluid, the existence of conserved genomic contexts suggests important loci of co-regulation. Could it be in these gene clusters that a possible link between growth and surface expansion is found? To answer this question this thesis undertook three missions, firstly we established a genome comparison tool (www.GenCoDB.org) that will take advantage of the ever-growing availability of bacterial genomes to assist us in the analysis, comparison, and quantification of genome contexts. This will rely on novel strategies in order to: accommodate the breadth of genome data available in a computationally efficient manner, reduce the effect of sampling bias that plague most bacterial datasets and ensure candidates are considered significant for their evolutionary context. The availability of GenCoDB is sure to facilitate genomic context research in the microbiology community and improve accessibility to non-bioinformatics to this wellspring of important biological data. With the swath of genomic neighbourhood data, we then sought to understand and analyse the evolution of conserved gene clusters in order to narrow down possible volume-surface regulating candidates. By tracking the evolution of gene clusters throughout the Bacteria kingdom we found that co-orientation is strongly conserved, however, this does not influence the subsequent context around the cluster nor the expansion of the cluster. We found that vertical transmission and not horizontal gene transfer was found to be the driving factor of gene cluster occurrence in chromosomes and that the origin and terminus are hotspots for cluster maintenance. Finally, we found that despite the apparent frequency of operon organization in gene clusters, gene clusters appear to be maintained due to other selective pressures such as within-cluster protein-protein interactions and the essential status of their genes. We suggest that operons are a consequence and not a cause co-localization over evolutionary time. We identified a single gene cluster candidate that met all the requirements we believe are required for cell growth homeostasis of synchronized surface and volume expansion. These requirements were a broad conservation within Bacteria, and a connection between ribosome-associated proteins (growth) with cell envelope synthesizes. In agreement with our evolution studies we found that whilst the cluster was co-regulated this did not appear to be the selective pressure that brought these different processes together. Instead we found a potential role of genomic channelling, linking the production of pyrimidines with the synthesis of the cell envelope which is reliant on the co-localization of this cluster. Together, this work will forward the understanding of chromosome evolution in Bacteria and the potential implications of genomic context in metabolite utilization. It challenges the roles that operons and horizontal gene transfer play in the long-term evolution of gene order and it provides a new quantitative and statistical resource providing access to over 1.9 million gene neighbourhoods.

Hepatitis D virus (HDV) causes the most severe form of viral hepatitis, which may rapidly progress to liver cirrhosis and hepatocellular carcinoma (HCC). It has been estimated that 15&ndash, 20 million people worldwide are suffering from the chronic HDV infection. Currently, no effective therapies are available to treat acute or chronic HDV infection. The remarkable sequence variability of the HDV genome, particularly within the hypervariable region has resulted in the provisional classification of eight major genotypes and various subtypes. We have developed a specialized database, HDVdb (http://hdvdb.bio.wzw.tum.de/), which contains a collection of partial and complete HDV genomic sequences obtained from the GenBank and from our own patient cohort. HDVdb enables the researchers to investigate the genetic variability of all available HDV sequences, correlation of genotypes to epidemiology and pathogenesis. Additionally, it will contribute in understanding the drug resistant mutations and develop effective vaccines against HDV infection. The database can be accessed through a web interface that allows for static and dynamic queries and offers integrated generic and specialized sequence analysis tools, such as annotation, genotyping, primer prediction, and phylogenetic analyses.

The traces (digital evidence) created by users can be influenced by the parameters transmitted by the web server. HTTP header entries instruct the web browser or web server to perform certain functions. These include, for example, the criteria according to which content is to be cached on the client. If these effects are unknown to the investigators, this can be erroneously classified as manipulation. In addition, it is now being considered that new traces can be created by header entries that are not yet in the focus of the common investigation procedures. In this work, a demo application was used to investigate which parameters have an influence on the forensic investigation of traces of Mozilla Firefox.

Graphical abstract, N6-methyladenosine (m6A) is the methylation of the adenosine at the nitrogen-6 position, which is the most abundant RNA methylation modification and involves a series of important biological processes. Accurate identification of m6A sites in genome-wide is invaluable for better understanding their biological functions. In this work, an ensemble predictor named iRNA-m6A was established to identify m6A sites in multiple tissues of human, mouse and rat based on the data from high-throughput sequencing techniques. In the proposed predictor, RNA sequences were encoded by physical-chemical property matrix, mono-nucleotide binary encoding and nucleotide chemical property. Subsequently, these features were optimized by using minimum Redundancy Maximum Relevance (mRMR) feature selection method. Based on the optimal feature subset, the best m6A classification models were trained by Support Vector Machine (SVM) with 5-fold cross-validation test. Prediction results on independent dataset showed that our proposed method could produce the excellent generalization ability. We also established a user-friendly webserver called iRNA-m6A which can be freely accessible at http://lin-group.cn/server/iRNA-m6A. This tool will provide more convenience to users for studying m6A modification in different tissues.

Complexes between proteins are at the basis of almost every process in cells. Their study, from a structural perspective, has a pivotal role in understanding biological functions and, importantly, in drug development. X-ray crystallography represents the broadest source for the experimental structural characterization of protein-protein complexes. Correctly identifying the biologically relevant interface from the crystallographic ones is, however, not trivial and can be prone to errors. Over the past two decades, computational methodologies have been developed to study the differences of those interfaces and automatically classify them as biological or crystallographic. Overall, protein-protein interfaces show differences in terms of composition, energetics and evolutionary conservation between biological and crystallographic ones. Based on those observations, a number of computational methods have been developed for this classification problem, which can be grouped into three main categories: Energy-, empirical knowledge- and machine learning-based approaches. In this review, we give a comprehensive overview of the training datasets and methods so far implemented, providing useful links and a brief description of each method.

Background Epigenetic regulation is essential in regulating gene expression across a variety of biological processes. Many high-throughput sequencing technologies have been widely used to generate epigenetic data, such as histone modification, transcription factor binding sites, DNA modifications, chromatin accessibility, and etc. A large scale of epigenetic data is stored in NCBI Gene Expression Omnibus (GEO). However, it is a great challenge to reanalyze these large scale and complex data, especially for researchers who do not specialize in bioinformatics skills or do not have access to expensive computational infrastructure. Results GsmPlot can simply accept GSM IDs to automatically download NCBI data or can accept user’s private bigwig files as input to plot the concerned data on promoters, exons or any other user-defined genome locations and generate UCSC visualization tracks. By linking public data repository and private data, GsmPlot can spark data-driven ideas and hence promote the epigenetic research. Conclusions GsmPlot web server allows convenient visualization and efficient exploration of any NCBI epigenetic data in any genomic region without need of any bioinformatics skills or special computing resources. GsmPlot is freely available at https://gsmplot.deqiangsun.org/.

DNA N4-methylcytosine modification (4mC) plays an essential role in a variety of biological processes. Therefore, accurate identification the 4mC distribution in genome-scale is important for systematically understanding its biological functions. In this study, we present Deep4mcPred, a multi-layer deep learning based predictive model to identify DNA N4-methylcytosine modifications. In this predictor, we for the first time integrate residual network and recurrent neural network to build a multi-layer deep learning predictive system. As compared to existing predictors using traditional machine learning, our proposed method has two advantages. First, our deep learning framework does not need to specify the features when training the predictive model. It can automatically learn the high-level features and capture the characteristic specificity of 4mC sites, benefiting to distinguish true 4mC sites from non-4mC sites. On the other hand, our deep learning method outperforms the traditional machine learning predictors in performance by benchmarking comparison, demonstrating that the proposed Deep4mcPred is more effective in the DNA 4mC site prediction. Moreover, via experimental comparison, we found that attention mechanism introduced into the deep learning framework is useful to capture the critical features. Additionally, we develop a webserver implementing the proposed method for the academic use of research community, which is now available at http://server.malab.cn/Deep4mcPred.

Dissertation, RWTH Aachen University, 2020; Aachen 1 Online-Ressource (XIII, 163 Seiten) : Illustrationen, Diagramme (2020). = Dissertation, RWTH Aachen University, 2020, Human G Protein-Coupled Receptors (hGPCRs) are the most frequent drug target for FDA-approved drugs. However, only a small fraction of hGPCRs is targeted by these drugs indicating a huge untapped pharmacological potential. Unfortunately, the development of drugs binding to hGPCRs is limited by the lack of three-dimensional structural information for most targets. The use of structural bioinformatics together with molecular simulation is one strategy to overcome this issue. In this regard, our institute developed the hybrid Molecular Mechanics/Coarse-Grained (MM/CG) method, tailored for the prediction of ligand poses based on homology or experimental models of GPCRs with docked or co-crystallized ligands. In this thesis, I implemented the new Amber-based approach in order to replace the original, GROMOS-based, implementation of the MM/CG method. The exchange of the force field significantly simplified the system preparation but also improved the agreement of predicted ligand poses with all-atom molecular dynamics simulations, X-ray structures, and experimental mutagenesis and functional data. The higher potential for automation of the new method paved the way for the development of a fully automatic workflow for MM/CG simulations. The workflow was implemented into the "Hybrid MM/CG Webserver" (mmcg.grs.kfa-juelich.de) to facilitate access to this method for other groups and allow for a fast and reproducible preparation of MM/CG systems., Published by Aachen

CRISPR/Cas9 systems are an established tool in genome engineering. As double strand breaks caused by the standard Cas9-based knock-out techniques can be problematic in some organisms, new systems were developed that can efficiently create knock-outs without causing double strand breaks to elegantly sidestep these issues. The recently published CRISPR-BEST base editor system for actinobacteria is built around a C to T or A to G base exchange. These base editing systems however require additional constraints to be considered for designing the sgRNAs. Here, we present an updated version of the interactive CRISPy-web single guide RNA design tool https://crispy.secondarymetabolites.org/that was built to support “classical” CRISPR and now also CRISPR-BEST workflows.

Hybrid Molecular Mechanics/Coarse-Grained (MM/CG) simulations help predict ligand poses in human G protein-coupled receptors (hGPCRs), the most important protein superfamily for pharmacological applications. This approach allows the description of the ligand, the binding cavity, and the surrounding water molecules at atomistic resolution, while coarse-graining the rest of the receptor. Here, we present the Hybrid MM/CG Webserver (mmcg.grs.kfa-juelich.de) that automatizes and speeds up the MM/CG simulation setup of hGPCR/ligand complexes. Initial structures for such complexes can be easily and efficiently generated with other webservers. The Hybrid MM/CG server also allows for equilibration of the systems, either fully automatically or interactively. The results are visualized online (using both interactive 3D visualizations and analysis plots), helping the user identify possible issues and modify the setup parameters accordingly. Furthermore, the prepared system can be downloaded and the simulation continued locally.

Board games are on the rise and chess is no exception. However, in an increasingly digitalized world these board games lack something in comparison to digitalized games, being able to play with anyone anywhere. This project aimed to combine these two worlds by being a physical game of chess where one could play against an opponent from far away. CheckMate is a robot consisting of an acrylic frame and various electronic components, such as an electromagnet, two stepper motors, a Hall eect sensor and a WiFi module. The electromagnet and Hall eect sensor were able to move using a belt and pulley system. This allowed magnetic pieces to be identified and dragged across the board. The board then communicated the location of all the pieces on the board, using Wifi, to an website that also kept track on whose turn it was. The result of this project was a robot that was able to perform all the moves necessary on the chessboard as well as communicating to the website. When moving a piece from one location to another the piece repelled other pieces on its way. However, this was deemed to be acceptable since the pieces were not moved too large of a distance for the electromagnet to attract them when moved into its square. One move that the robot was not able to perform was castling. The results can therefore bee seen as a starting point toward further developments. Brädspels popularitet stiger och schack är inget undantag. Dock saknar brädspel de digitala spelens möjlighet att spela med vem som helst varsomhelst. Detta projekt ville bygga över klyftorna mellan dessa två världar genom att vara ett fysiskt schackspel med de digitala spelens möjligheter. CheckMate är en robot byggd av akrylplast och diverse elektroniska komponenter sådan som en elektromagnet, två stegmotorer, en halleektsensor och en WiFi-modul. Elektromagneten och halleektsensorn förflyttades via ett system av kuggremmar drivet av stegmotorerna. Elektromagneten användes för att flytta pjäserna på brädet medan halleektsensorn användes vid kartläggning av pjäsernas position på brädet. Brädet kommunicerade, via trådlöst nätverk, till en hemsida som användes för att spara och överföra pjäsernas positioner. Projektet resulterade i en robot som kunde göra alla motsvarande drag hämtat från hemsidan. Dock så repellerade en flyttande pjäs på de stationära pjäserna när den passerade. Detta ansågs dock vara acceptabelt då elektromagneten kunde föra tillbaka pjäserna när den befann sig i dess ruta. Något som projektet ej lyckades utföra var draget rockad. Resultatet av detta projekt kan ses som en startpunkt i en vidareutveckling eller en färdig produkt vid obesvärad spelning.

Background Adenosine-to-inosine RNA editing can markedly diversify the transcriptome, leading to a variety of critical molecular and biological processes in mammals. Over the past several years, researchers have developed several new pipelines and software packages to identify RNA editing sites with a focus on downstream statistical analysis and functional interpretation. Results Here, we developed a user-friendly public webserver named MIRIA that integrates statistics and visualization techniques to facilitate the comprehensive analysis of RNA editing sites data identified by the pipelines and software packages. MIRIA is unique in that provides several analytical functions, including RNA editing type statistics, genomic feature annotations, editing level statistics, genome-wide distribution of RNA editing sites, tissue-specific analysis and conservation analysis. We collected high-throughput RNA sequencing (RNA-seq) data from eight tissues across seven species as the experimental data for MIRIA and constructed an example result page. Conclusion MIRIA provides both visualization and analysis of mammal RNA editing data for experimental biologists who are interested in revealing the functions of RNA editing sites. MIRIA is freely available at https://mammal.deepomics.org.

Meiotic recombination caused by meiotic double-strand DNA breaks. In some regions the frequency of DNA recombination is relatively higher, while in other regions the frequency is lower: the former is usually called "recombination hotspot", while the latter the "recombination coldspot". Information of the hot and cold spots may provide important clues for understanding the mechanism of genome revolution. Therefore, it is important to accurately predict these spots. In this study, we rebuilt the benchmark dataset by unifying its samples with a same length (131 bp). Based on such a foundation and using SVM (Support Vector Machine) classifier, a new predictor called "iRSpot-Pse6NC" was developed by incorporating the key hexamer features into the general PseKNC (Pseudo K-tuple Nucleotide Composition) via the binomial distribution approach. It has been observed via rigorous cross-validations that the proposed predictor is superior to its counterparts in overall accuracy, stability, sensitivity and specificity. For the convenience of most experimental scientists, the web-server for iRSpot-Pse6NC has been established at http://lin-group.cn/server/iRSpot-Pse6NC, by which users can easily obtain their desired result without the need to go through the detailed mathematical equations involved.

Hormone-binding protein (HBP) is a kind of soluble carrier protein and can selectively and non-covalently interact with hormone. HBP plays an important role in life growth, but its function is still unclear. Correct recognition of HBPs is the first step to further study their function and understand their biological process. However, it is difficult to correctly recognize HBPs from more and more proteins through traditional biochemical experiments because of high experimental cost and long experimental period. To overcome these disadvantages, we designed a computational method for identifying HBPs accurately in the study. At first, we collected HBP data from UniProt to establish a high-quality benchmark dataset. Based on the dataset, the dipeptide composition was extracted from HBP residue sequences. In order to find out the optimal features to provide key clues for HBP identification, the analysis of various (ANOVA) was performed for feature ranking. The optimal features were selected through the incremental feature selection strategy. Subsequently, the features were inputted into support vector machine (SVM) for prediction model construction. Jackknife cross-validation results showed that 88.6% HBPs and 81.3% non-HBPs were correctly recognized, suggesting that our proposed model was powerful. This study provides a new strategy to identify HBPs. Moreover, based on the proposed model, we established a webserver called HBPred, which could be freely accessed at http://lin-group.cn/server/HBPred.

The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it

The concept Industry 4.0 is a top theme of recent times. Even if it represents the so-called 4th industrial revolution its main ideas could be used also to support the education of subjects from IT and automation. Furthermore, the basic IT and web technologies inherited by this concept are very well known to students. This paper introduces the embedded webserver of PLC and the options for its optimal utilization. The web server is essentially a simple and widely well-known technology, therefore it was chosen as an example.

The initiate site of DNA replication is called origins of replication (ORI) which is regulated by a set of regulatory proteins and plays important roles in the basic biochemical process during cell growth and division in all living organisms. Therefore, the study of ORIs is essential for understanding the cell-division cycle and gene expression regulation so that scholars can develop a new strategy against genetic diseases by using the knowledge of DNA replication. Thus, the accurate identification of ORIs will provide key clues for DNA replication research and clinical medicine. Although, the conventional experiments could provide accurate results, they are time-consuming and cost ineffective. On the contrary, bioinformatics-based methods can overcome these shortcomings. Especially, with the emergence of DNA sequences in the post-genomic era, it is highly expected to develop high throughput tools to identify ORIs based on sequence information. In this review, we will summarize the current progress in computational prediction of eukaryotic ORIs including the collection of benchmark dataset, the application of machine learning-based techniques, the results obtained by these methods, and the construction of web servers. Finally, we gave the future perspectives on ORIs prediction. The review provided readers with a whole background of ORIs prediction based on machine learning methods, which will be helpful for researchers to study DNA replication in-depth and drug therapy of genetic defect.

The merger of SCADA (supervisory control and data acquisition) and IoTs (internet of things) technologies allows end-users to monitor and control industrial components remotely. However, this transformation opens up a new set of attack vectors and unpredicted vulnerabilities in SCADA/IoT field devices. Proper identification, assessment, and verification of each SCADA/IoT component through advanced scanning and penetration testing tools in the early stage is a crucial step in risk assessment. The Omega2, a small Linux server from Onion&trade, is used to develop various SCADA/IoT systems and is a key component of nano power grid systems. In this paper, we report product level vulnerabilities of Onion Omega2 that we have uncovered using advanced vulnerability scanning tools. Through this research, we would like to assist vendors, asset owners, network administrators, and security professionals by creating an awareness of the vulnerabilities of Onion Omega2 and by suggesting effective mitigations and security best practices.

Background The discovery of functionally conserved proteins is a tough and important task in system biology. Global network alignment provides a systematic framework to search for these proteins from multiple protein-protein interaction (PPI) networks. Although there exist many web servers for network alignment, no one allows to perform global multiple network alignment tasks on users’ test datasets. Results Here, we developed a web server WebNetcoffee based on the algorithm of NetCoffee to search for a global network alignment from multiple networks. To build a series of online test datasets, we manually collected 218,339 proteins, 4,009,541 interactions and many other associated protein annotations from several public databases. All these datasets and alignment results are available for download, which can support users to perform algorithm comparison and downstream analyses. Conclusion WebNetCoffee provides a versatile, interactive and user-friendly interface for easily running alignment tasks on both online datasets and users’ test datasets, managing submitted jobs and visualizing the alignment results through a web browser. Additionally, our web server also facilitates graphical visualization of induced subnetworks for a given protein and its neighborhood. To the best of our knowledge, it is the first web server that facilitates the performing of global alignment for multiple PPI networks. Availability http://www.nwpu-bioinformatics.com/WebNetCoffee

Antioxidant proteins have been found closely linked to disease control for its ability to eliminate excess free radicals. Because of its medicinal value, the study of identifying antioxidant proteins is on the upsurge. Many machine-learning classifiers have performed poorly owing to the nonlinear and unbalanced nature of biological data. Recently, deep learning techniques showed advantages over many state-of-the-art machine learning methods in various fields. In this study, a deep learning based classifier was proposed to identify antioxidant proteins based on mixed g-gap dipeptide composition feature vector. The classifier employed deep autoencoder to extract nonlinear representation from raw input. The t-Distributed Stochastic Neighbor Embedding (t-SNE) was used for dimensionality reduction. Support vector machine was finally performed for classification. The classifier achieved F_1 score of 0.8842 and MCC of 0.7409 in 10-fold cross validation. Experimental results show that our proposed method outperformed the traditional machine learning methods and could be a promising tool for antioxidant protein identification. For the convenience of others’ scientific research, we have developed a user-friendly web server called IDAod for antioxidant protein identification, which can be accessed freely at http://bigroup.uestc.edu.cn/IDAod/.

Geographic Information Systems and Network Information Systems are important tools for our society, used for handling geographic spatial data and large information networks. It is therefore important to make sure such tools are of high quality. GIS/NIS applications typically deal with a lot of data, possibly resulting in heavy loads of network traffic. This work aims to evaluate two different communications protocols and serialization formats for client-server communications efficiency in GIS/NIS applications. Specifically, these are HTTP/1.1, HTTP/2, Java Object Serialization and Google's Protocol Buffers. They were each implemented directly into a commercial GIS/NIS environment and evaluated by measuring two signature server calls in the system. Metrics that were examined are call duration, HTTP overhead size and HTTP payload size. The results suggest that HTTP/2 and Google's Protocol Buffers outperform HTTP/1.1 and Java Object Serialization respectively. An 87% decrease in HTTP overhead size was achieved when switching from HTTP/1.1 to HTTP/2. The HTTP payload size is also shown to decrease with the use of Protocol Buffers rather than Java Object Serialization, especially for communications where data consist of many different object types. Concerning call duration, the results suggest that the choice of communications protocol is more significant than the choice of serialization format for communications containing little data, while the opposite is true for communications containing much data. Geografiska informationssystem och nätverksinformationssystem är viktiga redskap för vårt samhälle, vilka används för hantering av geografisk data och stora informationsnätverk. Det är därför viktigt att se till att sådana system är av hög kvalitet. GIS/NIS-applikationer behandlar vanligtvis stora mängder data, vilket kan resultera i mycket nätverkstrafik. I det här arbetet utvärderas två olika kommunikationsprotokoll och serialiseringsformat för kommunikationseffektivitet mellan klient och server i GIS/NIS-applikationer. Specifikt är dessa HTTP/1.1, HTTP/2, Java Objektserialisering och Googles Protocol Buffers. De implementerades var och en i en kommersiell GIS/NIS-miljö och utvärderades genom mätningar av två signaturanrop i systemet. De aspekter som observerades är kommunikationstiden, mängden HTTP-overhead och mängden HTTP-payload. Resultaten tyder på att HTTP/2 och Googles Protocol Buffers presterar bättre än HTTP/1.1 respektive Java Objektserialisering. En 87% minskning av mängden HTTP overhead uppnåddes då HTTP/1.1 ersattes med HTTP/2. En minskning av mängden HTTP payload observeras också med användning av Protocol Buffers snarare än Java Objektserialisering, särskilt för kommunikationer där data innehåller många olika objekttyper. Gällande kommunikationstiden tyder resultaten på att valet av kommunikationsprotokoll påverkar mer än valet av serialiseringsformat för kommunikationer med små mängder data, medan motsatsen gäller för kommunikationer med mycket data.

The recent trends of remote monitoring and controlling prove that embedded system has drastically changed the data acquisition. In today's busy life it becomes very difficult to monitor data continuously by users. So, concepts of threshold is use to provide any change in data to users by alert. A significant value is considered as threshold set by C program and shell scripts. If data crosses the threshold value embedded system activate alert system to send SMS to register client making system secure. The main core of this paper present dynamic internet protocol (IP) based ARM9 embedded Webserver (EWS) for data acquisition in scale down version Linux. Dynamic IP obtain for EWS through GPRS of USB modem attached with system. Information stored in EWS sent alert SMS to client. Client as well able to access real time data, otherwise also it is accessible all time. Updated Dynamic IP of EWS is obtained from static dummy server. Direct access between user and EWS reduces interaction delay. Analysis of time delay of interaction is done and provided results proving system is real time. Test results are verified for different dynamic IPs and presented.

O presente relatório de projeto tem como objetivo apresentar o projeto desenvolvido referente a conceção de um sistema de controlo e monitorização de apoio ao processo de injeção de plástico em moldes. O projeto foi realizado para a empresa SpeedTurtle - High Precision Machining, Engineering, Plastic Injection Tools, situada no concelho da Batalha, Leiria em parceria com o Instituto Politécnico de Leiria. O sistema de controlo e monitorização será responsável por comandar todo o processo de transformação da peça extraída do molde até o seu armazenamento e monitorizar de forma remota os parâmetros mais relevantes do processo de injeção e transformação da peça. É utilizada a plataforma de gestão de redes remotas SINEMA Remote Connect da Siemens AG AG, que permite a gestão de até 1024 dispositivos remotos através de ligações móveis VPN (Virtual Private Network) 4G, indo de encontro com as necessidades da empresa em termos de monitorização remota de parâmetros. Numa primeira fase iniciou-se o estudo das tecnologias envolvidas nos processos de injeção, como sensores utilizados, componentes principais do processo de injeção (máquina de injeção, molde de injeção), sistemas de monitorização já desenvolvidos e as redes públicas virtuais, VPNs. Numa segunda fase iniciou-se a elaboração dos fluxogramas do processo de automatização do ciclo principal e aquisição dos sinais dos sensores analógicos, criação dos Grafcets (Graphe Fonctionnel de Commande, Étapes Transitions) em simultâneo com a escolha dos equipamentos necessários, programação do controlador S7-1200, criação da página Webserver para monitorização remota e envio de dados para o servidor SINEMA. O sistema foi testado em ambiente de simulação com recurso ao software Tia Portal e PLCSim V13 e a página Webserver com recurso à um autómato S7-1200 real e o envio de dados para o servidor SINEMA com recurso ao software SocketTest simulando a conexão cliente-servidor. As configurações finais e testes servidor SINEMA serão realizadas aquando da fase de implementação prática do sistema na empresa.

Transcriptional profiling is a prevalent and powerful approach for capturing the response of crop plants to environmental stresses, e.g. response of rice to drought. However, functionally interpreting the resulting genome-wide gene expression changes is severely hampered by the large gaps in our genomic knowledge about which genes work together in cellular pathways/processes in rice. Here, we present a new web resource – RECoN – that relies on a network-based approach to go beyond currently limited annotations in delineating functional and regulatory perturbations in new rice stress transcriptome datasets generated by a researcher. To build RECoN, we first enumerated 1,744 stress-specific gene modules covering 28,421 rice genes (>72% of the genes in the genome). Each module contains a group of genes tightly coexpressed across a large number of environmental conditions and, thus, is likely to be functionally coherent. When a user provides a new differential expression profile, RECoN identifies modules substantially perturbed in their experiment and further suggests deregulated functional and regulatory mechanisms based on the enrichment of current annotations within the predefined modules. We demonstrate the utility of this resource by analyzing new drought transcriptomes of rice in three developmental stages, which revealed large-scale insights into the cellular processes and regulatory mechanisms involved in common and stage-specific drought responses. RECoN enables biologists to functionally explore new data from all abiotic stresses on a genome-scale and to uncover gene candidates, including those that are currently functionally uncharacterized, for engineering stress tolerance.

Kebakaran hutan merupakan bencana yang dapat merusak lingkungan dan mengancam kelangsungan hidup hewan dan manusia. Proses pemadaman kebakaran hutan menjadi lebih mudah apabila kebakaran dapat dideteksi dengan cepat saat besarnya api masih terkontrol. Teknologi Wireless Sensor Network (WSN) dapat diaplikasikan dalam sistem pendeteksi dini kebakaran hutan dan dapat memonitoring kondisi suatu area secara realtime. Tujuan dari penelitian ini adalah dilakukannya komunikasi Wireless Sensor Network antara node sensor dan webserver untuk memetakan titik api kebakaran hutan. Pada penelitian ini digunakan tiga node sensor dan satu webserver dengan menggunakan modul xbee s1 dan protokol digimesh untuk membentuk jaringan yang terhubung secara wireless. Webserver diimplementasikan pada raspberry pi 2. Hasil pengujian menunjukkan setiap node sensor dapat mengirimkan sinyal kebakaran kepada webserver. Jarak maksimum antar modul xbee s1 adalah 28 meter dengan sinyal RSSI local sebesar -57 dBm dan sinyal RSSI remote sebesar -60 dBm. Node sensor yang tidak terjangkau langsung dengan wevserver akan mengirimkan sinyal secara berurutan ke node sensor yang lebih dekat untuk menyampaikan sinyal ke webserver. Webserver dapat menyimpan kondisi setiap node sensor kedalam database dan memetakan area kebakaran yang terintegrasi dengan google maps.

Bisnis binatu (laundry) atau bisnis jasa cuci pakaian merupakan bisnis yang menggiurkan saat sekarang ini. Proses layanan binatu umumnya terdiri dari pendaftaran, pengolahan, dan pengambilan pakaian. Proses ini memiliki banyak kekurangan yaitu pendaftaran manual tidak efektif dan efisien, pengolahan pakaian hanya diketahui oleh penyedia layanan binatu, dan pelanggan tidak mengetahui pakaian telah selesai. Ditengah persaingan bisnis yang begitu ketat, pelayanan konsumen merupakan suatu hal yang sangat penting. Penyedia jasa dituntut untuk berinovasi untuk menyediakan layanan jasa yang efektif dan efisien. Oleh karena itu pada penelitian ini merancang dan merealisasikan otomatisasi pelayanan binatu berbasis raspberry pi. Sistem ini menggunakan timbangan digital berbasis load cell, teknologi radio frequency identification (RFID) sebagai masukan data otomatis, Raspberry Pi sebagai pusat dari pengolahan basis data (database), dan webserver sebagai pusat informasi bagi pelanggan. Hasil penelitian menghasilkan beberapa kesimpulan. Timbangan digital memiliki eror rata-rata 0,88 %, metode RFID dapat memasukan data pelanggan secara otomatis dengan metode pengambilan nomor identitas jenis hex 8 digit, Raspberry Pi dapat mengakomodasi aplikasi yang efektif dan efisien untuk menyimpan data pelanggan secara otomatis dengan pemakaian CPU rata-rata 5%, dan webserver yang digunakan dapat menyediakan informasi layanan binatu bagi pelanggan.