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Idiotype-based therapeutics have failed to deliver their promise, necessitating rethinking of the concept and its potential to develop a viable immunotherapy method. The idiotype based hypothesis is discussed in this paper in order to produce effective anti-idiotype vaccinations. Polyclonal anti-idiotype reagents have been shown to be more successful in animal models, and a better understanding of the immune response in humans supports the idea that polyclonal anti-idiotype vaccines will be more effective than monoclonal-based anti-idiotype vaccines. This innovative approach can be used to produce therapeutic antibodies in a Biotech-standard manner. The idiotype network has been tweaked in the lab to provide protection against a variety of microbiological diseases. Antibodies to image-idiotype antigens, both internal and non-internal, can elicit unique immune responses to antigens. The current outbreak of severe acute respiratory syndrome 2 (SARS-2) has presented a fantastic chance to use idiotype/anti-idiotype antibodies as a protective regimen, which might be used to treat COVID-19 patients. The development of various effective vaccinations has been crucial in the pandemic's management, but their effectiveness has been limited. In certain healthy people, the development of viral variations and vaccinations can be linked to rare off-target or hazardous effects, such as allergic responses, myocarditis and immune-mediated thrombosis and thrombocytopenia. Many of these occurrences are most likely immune-mediated. The current analysis reveals successful idiotype/anti-idiotype antibody uses in a variety of viral illnesses, emphazising their importance in the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Artificial neural networks (ANN) provide a range of powerful new techniques for solving problems in sensor data analysis, fault detection, process identification, and control and have been used in a diverse range of chemical engineering applications. This paper aims to provide a comprehensive review of various ANN applications within the field of chemical engineering (CE). It deals with the significant aspects of ANN (architecture, methods of developing and training, and modeling strategies) in correlation with various types of applications. A systematic classification scheme is also presented, which uncovers, classifies, and interprets the existing works related to the ANN methodologies and applications within the CE domain. Based on this scheme, 717 scholarly papers from 169 journals are categorized into specific application areas and general (other) applications, including the following topics: petrochemicals, oil and gas industry, biotechnology, cellular industry, environment, health and safety, fuel and energy, mineral industry, nanotechnology, pharmaceutical industry, and polymer industry. It is hoped that this paper will serve as a comprehensive state-of-the-art reference for chemical engineers besides highlighting the potential applications of ANN in CE-related problems and consequently enhancing the future ANN research in CE field. [ABSTRACT FROM AUTHOR]

Experiments were performed to find potential sources for enzyme production for the pulp and paper industry and for biological ethanol production by screening the cellulase, xylanase and β-xylosidase activities of 36 species of Penicillium isolated from various wood materials in Korea. Rice straw powder (RiceP), birchwood xylan (BirchX), and beechwood xylan (BeechX) were supplied as individual carbon sources for the Penicillium species. All Penicillium species tested in this study showed little cellulase activity, but some species exhibited remarkably high xylanase and β-xylosidase activities, as determined by a filter paper assay. P. oxalicum showed the greatest xylanase activity on RiceP (158.70 U ml-1). On the other hand, P. brevicompactum produced the highest active β-xylosidase on BirchX (6.25 U ml-1). [ABSTRACT FROM AUTHOR]

Tinnitus is an annoying ringing in the ears, in varying shades and intensities. Tinnitus can affect a person’s overall health and social well-being (e.g., sleep problems, trouble concentrating, anxiety, depression and inability to work). The diagnostic procedure of tinnitus usually consists of three steps: an audiological examination, psychoacoustic measurement, and a disability evaluation. All steps are performed by physicians, who use specialised hardware/software and administer questionnaires. This paper presents a system, to be used by patients, for the diagnosis and self-management of tinnitus. The system is made up of an app and a device. The app is responsible for executing – through the device – a part of the required audiological and psychoacoustic examinations, as well as administering questionnaires that evaluate disability. The paper reviews the quality of the automated audiometric reporting and the user experience provided by the app. Descriptive and inferential statistics were used to support the findings. The results show that automated reporting is comparable with that of physicians and that user experience was improved by re-designing and re-developing the acufenometry of the app. As for the user experience, two experts in Human-Computer Interaction evaluated the first version of the app: their agreement was good (Cohen’s K = 0.639) and the average rating of the app was 1.43/2. Also patients evaluated the app in its initial version: the satisfactory tasks (audiometry and questionnaires) were rated as 4.31/5 and 4.65/5. The unsatisfactory task (acufenometry) was improved and the average rating increased from 2.86/5 to 3.96/5 (p = 0.0005). Finally, the general usability of the app was increased from the initial value of 73.6/100 to 85.4/100 (p = 0.0003). The strengths of the project are twofold. Firstly, the automated reporting feature, which – to the best of our knowledge – is the first attempt in this area. Secondly, the overall app usability, which was evaluated and improved during its development. In summary, the conclusion drawn from the conducted project is that the system works as expected, and despite some weaknesses, also the replication of the device would not be expensive, and it can be used in different scenarios.

The emergence of agricultural biotechnology and the subsequent introduction of genetically modified organisms (GMOs) into the food system have been among the most controversial issues surrounding the increasingly scrutinized agri-food system. They have received considerable attention in the economics literature with the main focus being on the optimal regulatory response to products of biotechnology. This paper builds on the literature on the regulation of products of biotechnology by placing the analysis of labeling decisions in a multi-country context. Specifically, the objective of this study is to examine the effect of the strategic interdependence between countries on their regulatory responses to products of biotechnology. The paper analyzes the strategic effects of national regulatory decisions on labeling of GM products and identifies the determinants of the non-cooperative Nash equilibrium labeling regimes in a small number of producing countries that supply the world market of an agricultural product. Analytical results show that the Nash equilibrium configuration of labeling regimes in countries that have adopted the GM technology depends on (i) the distribution of consumer preferences and the level of consumer aversion to GM products; (ii) the size of the segregation and labeling costs in these countries; (iii) the relative productive efficiency and the cost effectiveness of the GM technology; (iv) the market power of the life science companies; and (v) the strength of intellectual property rights in these countries. [ABSTRACT FROM AUTHOR]

For this special issue, we collected 8 high quality and breaking research papers on bioinspired and biobased chemistry and materials that were presented in the conference. Keywords: Biobased chemistry and materials; bioinspiration; biomimetics; biomimicry; bionic surfaces and interfaces; biotechnology; molecular architectures; nanobiocatalysts; nanotechnology; NICE 2020; smart technology; sustainable energy EN Biobased chemistry and materials bioinspiration biomimetics biomimicry bionic surfaces and interfaces biotechnology molecular architectures nanobiocatalysts nanotechnology NICE 2020 smart technology sustainable energy 1245 1246 2 11/29/21 20211101 NES 211101 As with the previous editions of NICE Conference, the aim of the 5th International Conference on Bioinspired and Biobased Chemistry & Materials (NICE 2020 Conference) is to provide a venue to experts, researchers, managers, manufacturers and policy makers from different countries and with different scientific backgrounds a place for the exchange of ideas, the open discussion of current research problems and the development of new ideas and collaborations with the aim of sustainable, green, and environmentally friendly solutions to material challenges that will have a lasting impact for generations. Bioinspiration, biomimetics, biotechnology, nanotechnology, NICE 2020, smart technology, Biobased chemistry and materials, bionic surfaces and interfaces, biomimicry, molecular architectures, nanobiocatalysts, sustainable energy. [Extracted from the article]

This paper shows how some existing refining technologies such as fluid catalytic cracking (FCC) can be modified to process bio-oil, derived from agricultural lignocellulosic wastes such as the sugar cane straw. Tests carried out in demonstration scale (150 kg/h) show the potential of these alternative materials to produce lignocellulosic gasoline or aromatic compounds, suitable to the petrochemical industry. [ABSTRACT FROM AUTHOR]

This paper employs a partial equilibrium trade framework to show that biofuel policy can substitute for traditional agricultural policy intended to boost farm welfare. It also shows how food market volatility can induce periods of boom and bust in the ethanol industry, causing episodes of bankruptcy and reduced capital investment. This paper further models the effects of two specific technological innovations—cellulosic ethanol and agricultural biotechnology—on food and fuel markets and demonstrates that technology can reduce ethanol market volatility. A parameterized model is used to characterize the impacts of biofuels on food and fuel markets. [ABSTRACT FROM AUTHOR]

As stated by World Health Organization (WHO) report, 246 million individuals have suffered with diabetes disease over worldwide and it is anticipated that by 2025 this estimation can cross 380 million. So, the proper and quick diagnosis of this disease is turned into a significant challenge for the machine learning researchers. This paper aims to design a robust model for diagnosis of diabetes using a hybrid approach of Chaotic-Jaya (CJaya) algorithm with Extreme Learning Machine (ELM), which is named as CJaya-ELM. In this paper, Jaya algorithm with Chaotic learning approach is used to optimize the random parameters of ELM classifier. Here, to assess the efficacy of the designed model, Pima Indian diabetes dataset is considered. Here, the designed model CJaya-ELM, has been compared with basic ELM, Teaching Learning Based Optimization algorithm (TLBO) optimized ELM (TLBO-ELM), Multi-Layer Perceptron (MLP), Jaya algorithm optimized MLP (Jaya-MLP), TLBO algorithm optimized MLP (TLBO-MLP) and CJaya algorithm optimized MLP models. CJaya-ELM model resulted in the highest testing accuracy of 0.9687, sensitivity of 1, specificity of 0.9688 with 0.9782 area under curve (AUC) value. Results reveal that CJaya-ELM model effectively classifies both the positive and negative samples of Pima and outperforms the competitors.

Genetic variance within the genotype of population and its mapping to phenotype variance in a systematic and high throughput manner is of interest for biodiversity and breeding research. Beside the established and efficient high throughput genotype technologies, phenotype capabilities got increased focus in the last decade. This results in an increasing amount of phenotype data from well scaling, automated sensor platform. Thus, data stewardship is a central component to make experimental data from multiple domains interoperable and re-usable. To ensure a standard and comprehensive sharing of scientific and experimental data among domain experts, FAIR data principles are utilized for machine read-ability and scale-ability. In this context, BrAPI consortium, provides a comprehensive and commonly agreed FAIRed guidelines to offer a BrAPI layered scientific data in a RESTful manner. This paper presents the concepts, best practices and implementations to meet these challenges. As one of the worlds leading plant research institutes it is of vital interest for the IPK-Gatersleben to transform legacy data infrastructures into a bio-digital resource center for plant genetics resources (PGR). This paper also demonstrates the benefits of integrated database back-ends, established data stewardship processes, and FAIR data exposition in a machine-readable, highly scalable programmatic interfaces.

Given the absence of progress toward a multilateral agreement on trade liberalization in the WTO's Doha Round, countries are attempting to gain the perceived gains from trade through the negotiation of preferential trade agreements. One of the most ambitious attempts to negotiate a preferential agreement is the Trans Pacific Partnership (TPP) which encompasses 12 countries across the Pacific including both the US and Japan. The TPP members account for approximately 40 % of global GDP. One of the most difficult issues in current international trade policy is the regulation of trade in the products of modern agricultural biotechnology. This question was on the negotiating agenda of the TPP. The objective of this paper is to lay out the major issues in the trade of products of modern agricultural biotechnology and examines the regulatory regimes for biotechnology in the 12 TPP countries. It finds that there is a significant divergence in the approaches to regulating genetically modified organisms (GMOs) across the TPP countries. As a result, the development of a harmonized regulatory regime to govern trade in GMOs was impossible directly in the TPP. A forum where the development of a harmonized system could potentially be undertaken was, however, agreed in the TPP. [ABSTRACT FROM AUTHOR]

Proteins are important parts of the biological structures and encode a lot of biological information. Protein–protein interaction network alignment is a model for analyzing proteins that helps discover conserved functions between organisms and predict unknown functions. In particular, multi-network alignment aims at finding the mapping relationship among multiple network nodes, so as to transfer the knowledge across species. However, with the increasing complexity of PPI networks, how to perform network alignment more accurately and efficiently is a new challenge. This paper proposes a new global network alignment algorithm called Simulated Annealing Multiple Network Alignment (SAMNA), using both network topology and sequence homology information. To generate the alignment, SAMNA first generates cross-network candidate clusters by a clustering algorithm on a k-partite similarity graph constructed with sequence similarity information, and then selects candidate cluster nodes as alignment results and optimizes them using an improved simulated annealing algorithm. Finally, the SAMNA algorithm was experimented on synthetic and real-world network datasets, and the results showed that SAMNA outperformed the state-of-the-art algorithm in biological performance.

Epilepsy is a neurological disorder (the third most common, following stroke and migraines). A key aspect of its diagnosis is the presence of seizures that occur without a known cause and the potential for new seizures to occur. Machine learning has shown potential as a cost-effective alternative for rapid diagnosis. In this study, we review the current state of machine learning in the detection and prediction of epileptic seizures. The objective of this study is to portray the existing machine learning methods for seizure prediction. Internet bibliographical searches were conducted to identify relevant literature on the topic. Through cross-referencing from key articles, additional references were obtained to provide a comprehensive overview of the techniques. As the aim of this paper aims is not a pure bibliographical review of the subject, the publications here cited have been selected among many others based on their number of citations. To implement accurate diagnostic and treatment tools, it is necessary to achieve a balance between prediction time, sensitivity, and specificity. This balance can be achieved using deep learning algorithms. The best performance and results are often achieved by combining multiple techniques and features, but this approach can also increase computational requirements.

The paper outlines the concept of the human being as homo biotechnologicus. This concept is just one version of many possible human self-interpretations, since human beings can answer their own fundamental question of 'who are we?' simply using their 'human, all too human' self-descriptions. However, technology is a substantial part of the human being as a natural being, and biotechnology is, moreover, its root. The biotechnology of today's world means that humanity is set on a path to transcending its own human nature, with all the risky consequences that entails. The author considers these radical developments from the standpoint of posthumanism [ABSTRACT FROM AUTHOR]

Many important aspects of biological knowledge at the molecular level can be represented by pathways. Through their analysis, we gain mechanistic insights and interpret lists of interesting genes from experiments (usually omics and functional genomic experiments). As a result, pathways play a central role in the development of bioinformatics methods and tools for computing predictions from known molecular-level mechanisms. Qualitative as well as quantitative knowledge about pathways can be effectively represented through biochemical networks linking the biochemical reactions and the compounds (e.g., proteins) occurring in the considered pathways. So, repositories providing biochemical networks for known pathways play a central role in bioinformatics and in systems biology. Here we focus on Reactome, a free, comprehensive, and widely used repository for biochemical networks and pathways. In this paper, we: (1) introduce a tool StARGate-X (STatistical Analysis of the Reactome multi-GrAph Through nEtworkX) to carry out an automated analysis of the connectivity properties of Reactome biochemical reaction network and of its biological hierarchy (i.e., cell compartments, namely, the closed parts within the cytosol, usually surrounded by a membrane); the code is freely available at https://github.com/marinoandrea/stargate-x; (2) show the effectiveness of our tool by providing an analysis of the Reactome network, in terms of centrality measures, with respect to in- and out-degree. As an example of usage of StARGate-X, we provide a detailed automated analysis of the Reactome network, in terms of centrality measures. We focus both on the subgraphs induced by single compartments and on the graph whose nodes are the strongly connected components. To the best of our knowledge, this is the first freely available tool that enables automatic analysis of the large biochemical network within Reactome through easy-to-use APIs (Application Programming Interfaces).

Coherence has an important influence on the ability of a set of international regulations to function effectively. This paper examines the degree of coherence among the international regulations relevant to applications and impacts of biotechnology, and outlines problems that may arise from a lack of coherence among this regulatory set. [ABSTRACT FROM AUTHOR]

There is significant abuse of medical diagnostic technology in some Asian countries to select male fetuses and embryos over female fetuses, which leads to an imbalanced sex ration at birth. The paper discusses the ethics of sex selection, and reviews policies that have been used. Legal measures to prevent this in China and India are described, as well as the reasons that those efforts have not solved the problem. There are also growing uses of technology for sex selection in Nepal and Vietnam. The Republic of Korea has used policies and education to reverse preference for boys, and there is discussion of the reasons behind this. New partners and policies are required to overcome this serious abuse of biotechnology that is responsible for close to one hundred million missing girls in the world population. [ABSTRACT FROM AUTHOR]

AbstractWood is colonised and degraded by a variety of micro-organisms, the most efficient ones are wood-rotting basidiomycetes. Microbial decay processes cause damage to wooden constructions, but also have great potential as biotechnological tools to change the properties of wood surfaces and of sound wood. Standard methods to evaluate changes in infected wood, e.g., EN350-1 1994, are time-consuming. Rapid FT-NIR spectroscopic methods are also suitable for this purpose. In this paper, degradation experiments on surfaces of spruce (Picea abiesL. Karst) and beech (Fagus silvaticaL.) were carried out with white rot basidiomycetes or the ascomycete Hypoxylon fragiforme. Experiments with brown rot or soft rot caused by Chaetomium globosumwere also performed. FT-NIR spectra collected from the degraded wood were subjected to principal component analysis. The lignin content and mass loss of the specimens were estimated based on univariate or multivariate data analysis (partial least squares regression). [ABSTRACT FROM AUTHOR]

GMOs have brought new concerns into an already challenged world trading system. This paper considers the jointly enodogenous formation of GMO-related standards and sub-global trading agreements. Standards are understood as tolerance levels for GMOs. Sub-global trading agreements may be either formal agreements between countries sanctioned by the WTO, or they may be implicit agreements, e.g. a developing country accepting the U.S. standards. We develop a theoretical model of standard formation and agreement formation. In autarky, national standards reflect the preferences of domestic consumers. The possibility of gains from trade encourages countries to modify their standards to facilitate trade with other countries having similar standards. Whether or not a country engages in trade depends on the magnitude and nature of the gains from trade - e.g. economies of scale, greater variety for consumers, etc. - and the degree of standard modification required for trade. If the gains from trade are sufficient, countries will compromise or harmonize standards to achieve these gains. In the case of countries of similar size (bargaining power), compromise may be feasible. In the case of countries of different size, harmonization of the smaller country's standard to that of the larger country may be more likely. The case of the European Union's de facto prohibition on trade in GMOs is represented as a case in which the gains from trade are insufficient to catalyze a compromise position. Analogously, the North American refusal to restrict or prohibit GMOs indicates that the gains from trade with Europe are insufficient to compensate for this change in standard. In the absence of a common global standard, countries with similar preferences cluster into smaller clubs to capture at least some gains from trade. [ABSTRACT FROM AUTHOR]

In July 2003, the European Parliament voted on amendments to the European Union's (EU) system of regulation for agricultural biotechnology, most notably the rules for mandatory labeling of food products that contain traces of genetically modified (GM) ingredients. The expectation is that approval of these changes in EU regulations will result in the moratorium on approval of new GM crops, formalized by the Council of the European Union in 1999, being lifted. Despite the approval of these amendments, in August, the US, along with Canada and Argentina, requested the formation of a WTO dispute panel to make a ruling on the EU's failure to approve marketing of a number of GM crops. This paper addresses the issue of whether there is any legitimacy in the EU's precautionary approach to biotechnology regulation, or whether their regulatory approach is trade distorting, and, hence, likely to be found in violation of WTO agreements. First the background to the debate in the EU and US over biotechnology is reviewed, paying particular attention to recent public discussion in the UK where the government has undertaken an extensive public consultation process over regulation of GM crops. Second, the EU's approach to biotechnology regulation is outlined and compared to that in the US, and the analytical foundations of the precautionary principle are reviewed. Third, how GM regulations fit into the rules of the WTO is outlined, along with a discussion of the nature of the US's WTO filing. [ABSTRACT FROM AUTHOR]

This paper argues that current forms of agricultural biotechnology have significant potential for developing countries; the challenge is to realize this potential. We develop a conceptual model that explains why the yield effects of GMVs (genetically modified varieties) tend to be significant and reduce chemical use, contributing to human welfare, and present results from empirical studies that support these findings. We demonstrate that the adoption of GMVs might not necessarily lead to elimination of many varieties. Instead, crop biodiversity may be enhanced. Finally, we discuss how IPR constraints can be addressed, and new institutions that are already emerging may be used to allow developing countries more access to IPRs. [ABSTRACT FROM AUTHOR]

A number of studies show that consumers are willing to pay premiums for GM-Free foods. In this paper, we examine the effect, if any, that GM-Free messages have on product selection by the consumer. We made sample products which differed in the use of the labels and conducted two experiments: a choice experiment and a memory recall experiment. The result of out choice experiment demonstrates that the consumer who shows general concern about GM foods without relevant biotech knowledge responds to GM-Free messages on front labels. On the other hand, the result of our memory recall experiment shows that the consumer with relevant biotech knowledge uses the product information on the back label. Thus, firms can positively influence the product selection of biotech un-savvy consumers by placing GM-Free messages on the front labels. [ABSTRACT FROM AUTHOR]

With an ever increasing amount of research data available, it becomes constantly more important to possess data literacy skills to benefit from this valuable resource. An integrative course was developed to teach students the fundamentals of data literacy through an engaging genome sequencing project. Each cohort of students performed planning of the experiment, DNA extraction, nanopore sequencing, genome sequence assembly, prediction of genes in the assembled sequence, and assignment of functional annotation terms to predicted genes. Students learned how to communicate science through writing a protocol in the form of a scientific paper, providing comments during a peer-review process, and presenting their findings as part of an international symposium. Many students enjoyed the opportunity to own a project and to work towards a meaningful objective.

At the present, coding sequence (CDS) has been discovered and larger CDS is being revealed frequently. Approaches and related tools have also been developed and upgraded concurrently, especially for phylogenetic tree analysis. This paper proposes an integrated automatic Taverna workflow for the phylogenetic tree inferring analysis using public access web services at European Bioinformatics Institute (EMBL-EBI) and Swiss Institute of Bioinformatics (SIB), and our own deployed local web services. The workflow input is a set of CDS in the Fasta format. The workflow supports 1,000 to 20,000 numbers in bootstrapping replication. The workflow performs the tree inferring such as Parsimony (PARS), Distance Matrix - Neighbor Joining (DIST-NJ), and Maximum Likelihood (ML) algorithms of EMBOSS PHYLIPNEW package based on our proposed Multiple Sequence Alignment (MSA) similarity score. The local web services are implemented and deployed into two types using the Soaplab2 and Apache Axis2 deployment. There are SOAP and Java Web Service (JWS) providing WSDL endpoints to Taverna Workbench, a workflow manager. The workflow has been validated, the performance has been measured, and its results have been verified. Our workflow’s execution time is less than ten minutes for inferring a tree with 10,000 replicates of the bootstrapping numbers. This paper proposes a new integrated automatic workflow which will be beneficial to the bioinformaticians with an intermediate level of knowledge and experiences. The all local services have been deployed at our portal http://bioservices.sci.psu.ac.th

This paper describes the design philosophy for our cloud-based virtual reality (VR) co-creation environment (CCE) for molecular modeling. Using interactive VR simulation can provide enhanced perspectives in molecular modeling for intuitive live demonstration and experimentation in the CCE. Then the use of the CCE can enhance knowledge creation by bringing people together to share and create ideas or knowledge that may not emerge otherwise. Our prototype CCE discussed here, which was developed to demonstrate our design philosophy, has already enabled multiple members to log in and touch virtual molecules running on a cloud server with no noticeable network latency via real-time artificial intelligence techniques. The CCE plays an essential role in the rational design of molecular robot parts, which consist of bio-molecules such as DNA and protein molecules.

Hypergraph, as a generalization of the notions of graph and simplicial complex, has gained a lot of attention in many fields. It is a relatively new mathematical model to describe the high-dimensional structure and geometric shapes of data sets. In this paper,we introduce the neighborhood hypergraph model for graphs and combine the neighborhood hypergraph model with the persistent (embedded) homology of hypergraphs. Given a graph,we can obtain a neighborhood complex introduced by L. Lovász and a filtration of hypergraphs parameterized by aweight function on the power set of the vertex set of the graph. Theweight function can be obtained by the construction fromthe geometric structure of graphs or theweights on the vertices of the graph. We show the persistent theory of such filtrations of hypergraphs. One typical application of the persistent neighborhood hypergraph is to distinguish the planar square structure of cisplatin and transplatin. Another application of persistent neighborhood hypergraph is to describe the structure of small fullerenes such as C20. The bond length and the number of adjacent carbon atoms of a carbon atom can be derived from the persistence diagram. Moreover, our method gives a highly matched stability prediction (with a correlation coefficient 0.9976) of small fullerene molecules.

Core facilities have to offer technologies that best serve the needs of their users and provide them a competitive advantage in research. They have to set up and maintain instruments in the range of ten to a hundred, which produce large amounts of data and serve thousands of active projects and customers. Particular emphasis has to be given to the reproducibility of the results. More and more, the entire process from building the research hypothesis, conducting the experiments, doing the measurements, through the data explorations and analysis is solely driven by very few experts in various scientific fields. Still, the ability to perform the entire data exploration in real-time on a personal computer is often hampered by the heterogeneity of software, the data structure formats of the output, and the enormous data sizes. These impact the design and architecture of the implemented software stack. At the Functional Genomics Center Zurich (FGCZ), a joint state-of-the-art research and training facility of ETH Zurich and the University of Zurich, we have developed the B-Fabric system, which has served for more than a decade, an entire life sciences community with fundamental data science support. In this paper, we sketch how such a system can be used to glue together data (including metadata), computing infrastructures (clusters and clouds), and visualization software to support instant data exploration and visual analysis. We illustrate our in-daily life implemented approach using visualization applications of mass spectrometry data.

This paper considers a mathematical model that accounts for the hematological disorders of blood in its flow in human arteries. Blood is described as a Newtonian fluid but with its viscosity as a function of the hematocrit, plasma viscosity, and shape factor of the red blood cells. The artery is modeled as a flexible circular pipe with the blood flow as oscillatory. This model is solved using HAM (Homotopy Analysis Method), an approximate analytical method, and we computed expressions for wall shear stress (WSS) and volumetric flow rate. With the help of publicly available data, blood flow in the human femoral artery for male and female populations aged 19 to 60 and above years is simulated for healthy, anemia, and polycythemia cases. The model projected a significant difference in the mean volumetric flow rates in the conditions mentioned above. Results also indicated that the mean WSS of healthy and anemic populations are not significantly different. However, a significant difference in the mean has been observed in healthy and polycythemic conditions. Furthermore, a 33.3% decrease in hematocrit value from that in the normal range (taken as 0.45) of a healthy population has increased the flow rate by 33.5%. For a value 33.3% above 0.45, there is a decrease of 42.7% in the flow rate.

No Abstract available [ABSTRACT FROM AUTHOR]

In this paper, we study the dynamical effects of timely and delayed diagnosis on the spread of COVID-19 in Ghana during its initial phase by using reported data from March 12 to June 19, 2020. The estimated basic reproduction number, ℛ0, for the proposed model is 1.04. One of the main focus of this study is global stability results. Theoretically and numerically, we show that the disease persistence depends on ℛ0. We carry out a local and global sensitivity analysis. The local sensitivity analysis shows that the most positive sensitive parameter is the recruitment rate, followed by the relative transmissibility rate from the infectious with delayed diagnosis to the susceptible individuals. And that the most negative sensitive parameters are: self-quarantined, waiting time of the infectious for delayed diagnosis and the proportion of the infectious with timely diagnosis. The global sensitivity analysis using the partial rank correlation coefficient confirms the directional flow of the local sensitivity analysis. For public health benefit, our analysis suggests that, a reduction in the inflow of new individuals into the country or a reduction in the inter community inflow of individuals will reduce the basic reproduction number and thereby reduce the number of secondary infections (multiple peaks of the infection). Other recommendations for controlling the disease from the proposed model are provided in Section 7.

In this paper we present how the process modeling and execution tools iPM and iPE can be used to model and execute biological processes. The main focus of this paper is on the flexibility of iPM and iPE with respect to the customization to the biological application domain. We will demonstrate the flexibility of our modeling methodology by giving two examples: Modeling the invocation semantics of web services used in the biological application domain and the processing of streamed data.

Sequencing technologies has provided the basis of most modern genome sequencing studies due to its high base-level accuracy and relatively low cost. One of the most demanding step is mapping reads to the human reference genome. The reliance on a single reference human genome could introduce substantial biases in downstream analyses. Pangenomic graph reference representations offer an attractive approach for storing genetic variations. Moreover, it is possible to include known variants in the reference in order to make read mapping, variant calling, and genotyping variant-aware. Only recently a framework for variation graphs, vg [Garrison E, Adam MN, Siren J, et al. Variation graph toolkit improves read mapping by representing genetic variation in the reference. Nat Biotechnol 2018;36:875–9], have improved variation-aware alignment and variant calling in general. The major bottleneck of vg is its high cost of reads mapping to a variation graph. In this paper we study the problem of SNP calling on a variation graph and we present a fast reads alignment tool, named VG SNP-Aware. VG SNP-Aware is able align reads exactly to a variation graph and detect SNPs based on these aligned reads. The results show that VG SNP-Aware can efficiently map reads to a variation graph with a speedup of 40× with respect to vg and similar accuracy on SNPs detection.

Ovarian cancer is the third leading cause of cancer-related deaths in India. Epigenetics mechanisms seemingly plays an important role in ovarian cancer. This paper highlights the crucial epigenetic changes that occur in POTEE that get hypomethylated in ovarian cancer. We utilized the POTEE paralog mRNA sequence to identify major motifs and also performed its enrichment analysis. We identified 6 motifs of varying lengths, out of which only three motifs, including CTTCCAGCAGATGTGGATCA, GGAACTGCC, and CGCCACATGCAGGC were most likely to be present in the nucleotide sequence of POTEE. By enrichment and occurrences identification analyses, we rectified the best match motif as CTTCCAGCAGATGT. Since there is no experimentally verified structure of POTEE paralog, thus, we predicted the POTEE structure using an automated workflow for template-based modeling using the power of a deep neural network. Additionally, to validate our predicted model we used AlphaFold predicted POTEE structure and observed that the residual stretch starting from 237-958 had a very high confidence per residue. Furthermore, POTEE predicted model stability was evaluated using replica exchange molecular dynamic simulation for 50 ns. Our network-based epigenetic analysis discerns only 10 highly significant, direct, and physical associators of POTEE. Our finding aims to provide new insights about the POTEE paralog.

Dengue is the most common mosquito-borne viral infection transmitted disease. It is due to the four types of viruses (DENV-1, DENV-2, DENV-3, DENV-4), which transmit through the bite of infected Aedes aegypti and Aedes albopictus female mosquitoes during the daytime. The first globally commercialized vaccine is Dengvaxia, also known as the CYD-TDV vaccine, manufactured by Sanofi Pasteur. This paper presents a Ross-type epidemic model to describe the vaccine interaction between humans and mosquitoes using an entomological mosquito growth population and constant human population. After establishing the basic reproduction number ℛ0, we present three control strategies: vaccination, vector control, and the combination of vaccination and vector control. We use Pontryagin’s minimum principle to characterize optimal control and apply numerical simulations to determine which strategies best suit each compartment. Results show that vector control requires shorter time applications in minimizing mosquito populations. Whereas vaccinating the primary susceptible human population requires a shorter time compared to the secondary susceptible human.

Biclustering is a non-supervised data mining technique used to analyze gene expression data, it consists to classify subgroups of genes that have similar behavior under subgroups of conditions. The classified genes can have independent behavior under other subgroups of conditions. Discovering such co-expressed genes, called biclusters, can be helpful to find specific biological features such as gene interactions under different circumstances. Compared to clustering, biclustering has two main characteristics: bi-dimensionality which means grouping both genes and conditions simultaneously and overlapping which means allowing genes to be in more than one bicluster at the same time. Biclustering algorithms, which continue to be developed at a constant pace, give as output a large number of overlapping biclusters. Visualizing groups of biclusters is still a non-trivial task due to their overlapping. In this paper, we present the most interesting techniques to visualize groups of biclusters and evaluate them.

It is well known that genomic materials (long DNA chains) of living organisms are often packed compactly under extreme confining conditions using macromolecular self-assembly processes but the general DNA packing mechanism remains an unsolved problem. It has been proposed that the topology of the packed DNA may be used to study the DNA packing mechanism. For example, in the case of (mutant) bacteriophage P4, DNA molecules packed inside the bacteriophage head are considered to be circular since the two sticky ends of the DNA are close to each other. The DNAs extracted from the capsid without separating the two ends can thus preserve the topology of the (circular) DNAs. It turns out that the circular DNAs extracted from bacteriophage P4 are non-trivially knotted with very high probability and with a bias toward chiral knots. In order to study this problem using a systematic approach based on mathematical modeling, one needs to introduce a DNA packing model under extreme volume confinement condition and test whether such a model can produce the kind of knot spectrum observed in the experiments. In this paper we introduce and study a model of equilateral random polygons con_ned in a sphere. This model is not meant to generate polygons that model DNA packed in a virus head directly. Instead, the average topological characteristics of this model may serve as benchmark data for totally randomly packed circular DNAs. The difference between the biologically observed topological characteristics and our benchmark data might reveal the bias of DNA packed in the viral capsids and possibly lead to a better understanding of the DNA packing mechanism, at least for the bacteriophage DNA. The purpose of this paper is to provide information about the knot spectrum of equilateral random polygons under such a spherical confinement with length and confinement ratios in a range comparable to circular DNAs packed inside bacteriophage heads.