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With its constitutive and functional characteristics, the intestinal microbiota plays a crucial role in the health condition of the animals. Variations in the composition and gene expression of the intestinal microbiota are associated with the risk of the onset of various pathologies of the gastrointestinal tract and chronic inflammatory intestinal diseases. The objectives of this study were to evaluate the variability in the composition of the intestinal microbiota of goats of different breeds (Sarda, Maltese, and Alpine) farmed in different flocks of the region of Ogliastra (Sardegna, Italy) and to assess whether the type of feeding (natural pasture grazing-based versus intensive) could affect the intestinal bacterial composition. We also evaluated possible differences in the composition of the intestinal microbiota between healthy and Caprine arthritis encephalitis (CAE)-affected goats. The economic damage caused by this pathology is due to the reduction in milk production, with infected animals having greater susceptibility to contract diseases. The results of our study highlighted a statistically significant difference (P = 0.001–0.005) in the intestinal bacterial composition between the intensively managed flock and the other natural pasture-based flock.g In particular, a significantly greater abundance of Acidoaminococcaceae in the intensive flock was obgserved. Furthermore, a significantly greater abundance of Prevotellaceae was found in two localities in which, out of a total of 29 animals, only four tested negative for CAE. From these data, we deduced that the presence of Prevotellaceae can be an indication of the disease. This difference could be attributed to the farming system, the Cardedu farm being the only intensive one, and to the geographical distance of this location from the other sampling sites. Therefore, the results of the present study suggest that extensive or intensive farm management may affect the intestinal microbiota of goats. [ABSTRACT FROM AUTHOR]

The influx of whole genome sequencing (WGS) data in the public health and clinical diagnostic sectors has created a need for data analysis methods and bioinformatics expertise, which can be a bottleneck for many laboratories. At Sciensano, the Belgian national public health institute, an intuitive and user-friendly bioinformatics tool portal was implemented using Galaxy, an open-source platform for data analysis and workflow creation. The Galaxy @Sciensano instance is available to both internal and external scientists and offers a wide range of tools provided by the community, complemented by over 50 custom tools and pipelines developed in-house. The tool selection is currently focused primarily on the analysis of WGS data generated using Illumina sequencing for microbial pathogen typing, characterization and outbreak detection, but it also addresses specific use cases for other data types. Our Galaxy instance includes several custom-developed 'push-button' pipelines, which are user-friendly and intuitive stand-alone tools that perform complete characterization of bacterial isolates based on WGS data and generate interactive HTML output reports with key findings. These pipelines include quality control, de novo assembly, sequence typing, antimicrobial resistance prediction and several relevant species-specific assays. They are tailored for pathogens with active genomic surveillance programs, and clinical relevance, such as Escherichia coli, Listeria monocytogenes, Salmonella spp. and Mycobacterium tuberculosis. These tools and pipelines utilize internationally recognized databases such as PubMLST, EnteroBase, and the NCBI National Database of Antibiotic Resistant Organisms, which are automatically synchronized on a regular basis to ensure up-to-date results. Many of these pipelines are part of the routine activities of Belgian national reference centers and laboratories, some of which use them under ISO accreditation. This resource is publicly available for noncommercial use at https://galaxy.sciensano.be/ and can help other laboratories establish reliable, traceable and reproducible bioinformatics analyses for pathogens encountered in public health settings. [ABSTRACT FROM AUTHOR]

Historical measurements, such as the measurement of the size of our Galaxy and distance to its center, are based on relatively simple assumptions that allow high-school students and undergraduate college students to explore and replicate the basic analysis of astronomical data. Here, I present a practical data analysis exercise that was developed to select Slovenian participants to the International Olympiad on Astronomy and Astrophysics (IOAA). The exercise guides students to discover the globular cluster distribution within our Galaxy, use basic knowledge of spherical astronomy and coordinate transformation, explore the night sky and develop basic skills for the analysis of astronomical data. [ABSTRACT FROM AUTHOR]

Since recent years, mass segregation driven by two-body relaxation in star clusters has been proposed to be measured by the so-called dynamical clock, A + , a measure of the area enclosed between the cumulative radial distribution of blue straggler stars and that of a reference population. Since star clusters spend their lifetime immersed in the gravitational potential of their host galaxy, they are also subject to the effects of galactic tides. In this work, I show that the A + index of a star cluster depends on both its internal dynamics in isolation and the effects of galactic tides. Mainly, I focused on the largest sample of open clusters harboring blue straggler stars with robust cluster membership. I found that these open clusters exhibit an overall dispersion of the A + index in diagnostic diagrams, whereas Milky Way globular clusters show a clear linear trend. However, as also experienced by globular clusters, A + values of open clusters show some dependence on their galactocentric distances, in the sense that clusters located closer or farther than ∼ 11 kpc from the Galactic center have larger and smaller A + values, respectively. This different response to two-body relaxation and galactic tides in globular and open clusters, which happen concurrently, can be due to their different masses. More massive clusters can protect their innermost regions from galactic tides more effectively. [ABSTRACT FROM AUTHOR]

Context: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is the central system in epigenomic exploration. Chromatin immunoprecipitation coupled with sequencing (ChIP-seq) is an important technology to identify the genome-wide location of DNA-binding proteins such as histones proteins, transcription factors, RNA polymerase, or any protein of interest. ChIP-seq has been used to study the binding sites and efficacy of drugs in cancer cell lines etc. Aims: In current research, breast cancer cell line data have been used to study the effect PADI2 (peptidyl arginine deiminase) gene in the progression of breast cancer. Further, this ChIP-seq data have also been used to study the binding site of Amanitin drug in breast cancer. Settings and Design: Breast cancer ChIP-seq data have been retrieved from the European Nucleotide Archive database with project Id PRJNA415426 short read archive. Four samples of FASTQ files were used and analyzed for the genome-wide analysis. Materials and Methods: Galaxy server (https://usegalaxy.org/) was used for complete ChIP-seq data analysis; different tools such as fast-quality control (QC), multi-QC, Bowtie2, model-based analysis of ChIP-sequencing, and ChIPseeker tools were used for motif enrichment and functional analysis. Motif analysis was done through the Multiple Expectation maximizations for Motif Elicitation database (https://meme-suite.org/meme/db/motifs). Results: Computational investigation demonstrates the binding sequences of the T47-D breast cancer cell line as TTTTGTATTTTTAGT, and this motif occurs 2123 times in the Homo Sapiens reference genome that is hg19. Conclusions: This research classifies the binding site and affinity of the T47-D human breast cancer cell line. Further, wet laboratory studies are required to verify the function of the predicted motifs and their importance in drug development or research in breast cancer. [ABSTRACT FROM AUTHOR]

The concept of steady-state solutions to the Navier–Stokes equation is defined. Such solutions extend the notion of stationary ones, diminish exponentially over time, and have a fixed spatial field of velocities and constant pressure in the absence of external fields. A way of constructing these solutions is considered, and the problem of Taylor vortices is solved. A mathematical model of a tornado is proposed, within which a steady-state solution is obtained as an eigenfunction of the problem in the form of a vortex. A model for the formation of the structure of a gas cloud is proposed, based on the Navier–Stokes equation. It is shown that spiral arms arise from flows of gas moving outward, due to the Coriolis force. It is proved that the number of arms is even and their structure is independent of the angular velocity of rotation. We obtain a formula for the twist angle of the spirals, depending on the cloud parameters for when . [ABSTRACT FROM AUTHOR]

Very recently, a straightforward method was proposed to understand galaxies and galactic clusters without using the very elusive dark matter concept. This method is called the κ -model. The main idea is to maintain the form of the usual physical laws, especially Newton's laws of motion when gravity is weak, but only by applying a local scaling procedure for the related lengths, distances, and velocities. This local scaling appears as a correspondence principle in the κ -model. In this model, the fundamental physical constants remain universal, i.e., they are independent of a point in space and of time. The κ -model is Newtonian in its essence, but there is a relativistic extension that can easily be built. The aim of the present paper is to detail the mathematical formalism supporting it. [ABSTRACT FROM AUTHOR]

Galaxies are observed to host magnetic fields with a typical total strength of around 15 μ G. A coherent large-scale field constitutes up to a few microgauss of the total, while the rest is built from strong magnetic fluctuations over a wide range of spatial scales. This represents sufficient magnetic energy for it to be dynamically significant. Several questions immediately arise: What is the physical mechanism that gives rise to such magnetic fields? How do these magnetic fields affect the formation and evolution of galaxies? In which physical processes do magnetic fields play a role, and how can that role be characterized? Numerical modelling of magnetized flows in galaxies is playing an ever-increasing role in finding those answers. We review major techniques used for these models. Current results strongly support the conclusion that field growth occurs during the formation of the first galaxies on timescales shorter than their accretion timescales due to small-scale turbulent dynamos. The saturated small-scale dynamo maintains field strengths at only a few percent of equipartition with turbulence. This is in contradiction with the observed magnitude of turbulent fields, but may be reconciled by the further contribution to the turbulent field of the large-scale dynamo. The subsequent action of large-scale dynamos in differentially rotating discs produces field strengths observed in low redshift galaxies, where it reaches equipartition with the turbulence and has substantial power at large scales. The field structure resulting appears consistent with observations including Faraday rotation and polarisation from synchrotron and dust thermal emission. Major remaining challenges include scaling numerical models toward realistic scale separations and Prandtl and Reynolds numbers. [ABSTRACT FROM AUTHOR]

Aim is to create a system that can precisely and efficiently classify stars and galaxies, which can at that point be utilized for different applications in astronomy and astrophysics. The objective of this project is to create a progressed framework for categorizing stars, galaxies, and quasars, while also evaluating various classification models to identify the most effective one. My hypothesis centered on the possibility of preparing a machine learning model to precisely classify stars, quasars and galaxies utilizing the dataset given by the Sloan Digital Sky Survey (SDSS) [25]. We aimed to accomplish ideal execution with balanced data sets. We have utilized machine learning calculation like Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), Decision Tree (DT). The proposed machine learning show can help astronomers in precisely classifying celestial bodies in the sky, possibly contributing to headways in our understanding of the universe. The proposed machine learning show can help astronomers in precisely classifying celestial bodies in the sky, possibly contributing to headways in our understanding of the universe. This research social suggestions have a huge effect on the logical community, not fair in space science but also in other zones that require to classify things accurately. [ABSTRACT FROM AUTHOR]

This white paper explores the detectability of intermediate-mass black holes (IMBHs) wandering in the Milky Way (MW) and massive local galaxies, with a particular emphasis on the role of AXIS. IMBHs, ranging within 10 3 − 6 M ⊙ , are commonly found at the centers of dwarf galaxies and may exist, yet undiscovered, in the MW. By using model spectra for advection-dominated accretion flows (ADAFs), we calculated the expected fluxes emitted by a population of wandering IMBHs with masses of 10 5 M ⊙ in various MW environments and extrapolated our results to massive local galaxies. Around 40 % of the potential population of wandering IMBHs in the MW can be detected in an AXIS deep field. We proposed criteria to aid with selecting IMBH candidates using already available optical surveys. We also showed that IMBHs wandering in >200 galaxies within 10 Mpc can be easily detected with AXIS when passing within dense galactic environments (e.g., molecular clouds and cold neutral medium). In summary, we highlighted the potential X-ray detectability of wandering IMBHs in local galaxies and provided insights for guiding future surveys. Detecting wandering IMBHs is crucial for understanding their demographics and evolution and the merging history of galaxies. This white paper is part of a series commissioned for the AXIS Probe Concept Mission; additional AXIS white papers can be found at the AXIS website. [ABSTRACT FROM AUTHOR]

We study the metallicity distribution and evolution in the galactic disk based on the largest sample of open star clusters in the galaxy. From the catalog of 1,879 open clusters in the range of galactocentric distance (RGC) from 4 to 20 kpc, we investigate the variation in metallicity in the galactic disk as functions of RGC, vertical distance (Z), and ages of the clusters. In the direction perpendicular to the galactic plane, the variation in metallicity is found to follow a stepped linear relation. We estimate a vertical metallicity gradient?????H" of -0.545 ± 0.046 dex kpc-1 for |Z| < 0.487 kpc and -0.075 ± 0.093 dex kpc-1 for 0.487 < |Z| < 1.8 kpc. On average, metallicity variations above and below the galactic plane are found to change at similar rates. The change in metallicity in the radial direction is also found to follow a two-function linear relation. We obtain a radial metallicity gradient ^^ of -0.070 ± 0.002 dex kpc-1 for 4.0 < RGC < 12.8 dRGC kpc and -0.005 ± 0.018 dex kpc-1 for 12.8 < RGC < 20.5 kpc, which clearly shows a strong variation in the metallicity gradient when moving from the inner to the outer galactic disk. The age-metallicity relation (AMR) is found to follow a steeper negative slope of -0.031 ± 0.006 dex Gyr-1 for clusters older than 240 Myr; however, there is some hint of positive metallicity age gradient for younger clusters. [ABSTRACT FROM AUTHOR]

Our main goal here is to conduct a comparative analysis between the well-known MOND theory and a more recent model called the κ -model. An additional connection, between the κ -model and two other novel MOND-type theories, Newtonian Fractional-Dimension Gravity (NFDG) and Refracted Gravity (RG), is likewise presented. All these models are built to overtake the DM paradigm, or at least to strongly reduce the dark matter content. Whereas they rely on different formalisms, however, all four seem to suggest that the universal parameter, a 0 , appearing in MOND theory could intrinsically be correlated to either the sole baryonic mean mass density (RG and κ -model) and/or to the dimension of the object under consideration (NFDG and κ -model). We then confer to parameter a 0 a more flexible status of multiscale parameter, as required to explain the dynamics together in galaxies and in galaxy clusters. Eventually, the conformal gravity theory (CFT) also seems to have some remote link with the κ -model, even though the first one is an extension of general relativity, and the second one is Newtonian in essence. The κ -model has been tested on a small sample of spiral galaxies and in galaxy clusters. Now, we test this model on a large sample of galaxies issued from the SPARC database. [ABSTRACT FROM AUTHOR]

The Scalar Field Dark Matter model has been known in various ways throughout its history; Fuzzy, BEC, Wave, Ultralight, Axion-like Dark Matter, etc. All of them consist in proposing that dark matter of the universe is a spinless field Φthat follows the Klein-Gordon (KG) equation of motion □Φ-dV/dΦ=0, for a given scalar field potential V. The difference between different models is sometimes the choice of the scalar field potential V. In the literature we find that people usually work in the non-relativistic, weak-field limit of the Klein- Gordon equation, where it transforms into the Schrödinger equation and the Einstein equations into the Poisson equation, reducing the KG-Einstein system, to the Schrödinger-Poisson system. In this paper, we review some of the most interesting achievements of this model from the historical point of view and its comparison with observations, showing that this model could be the last answer to the question about the nature of dark matter in the universe. [ABSTRACT FROM AUTHOR]

Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double-stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including the location of substrate binding sites, flexible domains, and the discovery of potential inhibitors. Here we present a series of new Galaxy tools and workflows for performing and analyzing molecular dynamics simulations of viral helicases. We first validate them by demonstrating recapitulation of data from previous simulations of Zika (NS3) and SARS-CoV-2 (NSP13) helicases in apo and complex with inhibitors. We further demonstrate the utility and generalizability of these Galaxy workflows by applying them to new cases, proving their usefulness as a widely accessible method for exploring antiviral activity. [ABSTRACT FROM AUTHOR]

Background In clinical research, data have to be accessible and reproducible, but the generated data are becoming larger and analysis complex. Here we propose a platform for Findable, Accessible, Interoperable, and Reusable (FAIR) data access and creating reproducible findings. Standardized access to a major genomic repository, the European Genome-Phenome Archive (EGA), has been achieved with API services like PyEGA3. We aim to provide a FAIR data analysis service in Galaxy by retrieving genomic data from the EGA and provide a generalized "omics" platform for FAIR data analysis. Results To demonstrate this, we implemented an end-to-end Galaxy workflow to replicate the findings from an RD-Connect synthetic dataset Beyond the 1 Million Genomes (synB1MG) available from the EGA. We developed the PyEGA3 connector within Galaxy to easily download multiple datasets from the EGA. We added the gene.iobio tool, a diagnostic environment for precision genomics, to Galaxy and demonstrate that it provides a more dynamic and interpretable view for trio analysis results. We developed a Galaxy trio analysis workflow to determine the pathogenic variants from the synB1MG trios using the GEMINI and gene.iobio tool. The complete workflow is available at WorkflowHub, and an associated tutorial was created in the Galaxy Training Network, which helps researchers unfamiliar with Galaxy to run the workflow. Conclusions We showed the feasibility of reusing data from the EGA in Galaxy via PyEGA3 and validated the workflow by rediscovering spiked-in variants in synthetic data. Finally, we improved existing tools in Galaxy and created a workflow for trio analysis to demonstrate the value of FAIR genomics analysis in Galaxy. [ABSTRACT FROM AUTHOR]

Galaxies are one of the most interesting and complex astronomical objects statistically due to their continuous diversification caused mainly due to incidents such as accretion, action, or mergers. Multivariate studies are one of the most useful tools to analyze these type of data and to understand various components of them. We study a sample of the local universe of Orlando 509 galaxies, imputed with a Predictive Mean Matching (PMM) multiple imputation algorithm, with the aim of classifying the galaxies into distinct clusters through k-medoids and k-mean algorithms and, in turn, performing a heuristic evaluation of the two partitioning algorithms through the percentage of misclassification observed. From the clustering algorithms, it was observed that there were four distinct clusters of the galaxies with misclassification of about 1.96 % . Also, comparing the percentage of misclassification heuristically k-means is a superior algorithm to k-medoids under fixed optimal sizes when the said category of galaxy datasets is concerned. By considering that galaxies are continuously evolving complex objects and using appropriate statistical tools, we are able to derive an explanatory classification of galaxies, based on the physical diverse properties of galaxies, and also establish a better method of partitioning when working on the galaxies. [ABSTRACT FROM AUTHOR]

Background: Galaxy is a web-based open-source platform for scientific analyses. Researchers use thousands of high-quality tools and workflows for their respective analyses in Galaxy. Tool recommender system predicts a collection of tools that can be used to extend an analysis. In this work, a tool recommender system is developed by training a transformer on workflows available on Galaxy Europe and its performance is compared to other neural networks such as recurrent, convolutional and dense neural networks. Results: The transformer neural network achieves two times faster convergence, has significantly lower model usage (model reconstruction and prediction) time and shows a better generalisation that goes beyond training workflows than the older tool recommender system created using RNN in Galaxy. In addition, the transformer also outperforms CNN and DNN on several key indicators. It achieves a faster convergence time, lower model usage time, and higher quality tool recommendations than CNN. Compared to DNN, it converges faster to a higher precision@k metric (approximately 0.98 by transformer compared to approximately 0.9 by DNN) and shows higher quality tool recommendations. Conclusion: Our work shows a novel usage of transformers to recommend tools for extending scientific workflows. A more robust tool recommendation model, created using a transformer, having significantly lower usage time than RNN and CNN, higher precision@k than DNN, and higher quality tool recommendations than all three neural networks, will benefit researchers in creating scientifically significant workflows and exploratory data analysis in Galaxy. Additionally, the ability to train faster than all three neural networks imparts more scalability for training on larger datasets consisting of millions of tool sequences. Open-source scripts to create the recommendation model are available under MIT licence at https://github.com/anuprulez/galaxy_tool_recommendation_transformers [ABSTRACT FROM AUTHOR]

The fertility of female cows is the main factor for the survival of dairy farming. This study was performed to determine the differentially expressed genes in fertility in Holstein cows using phenotypic data and next-generation sequencing (NGS) technology. Corpus luteum samples from 18 Holstein cows at up to two parturitions were used in two high and low fertility groups, three samples from each group were pooled together and a total of three biological samples from each were submitted for whole genome sequencing. The preparation and analysis steps were performed on the Galaxy 22.01 platform. DAVID (2021) database were used for gene ontology. The results of differential gene expression analysis in luteal tissue showed that 19 genes out of 13049 expressed transcripts had a significant difference in expression between high and low-fertility cows with an FDR-adjusted p-value (q-value) of less than 0.05. UBE3B, NIF3L1 and ORC2 genes were three functional marker genes that were more highly expressed in the corpus luteum of high-fertility cows. The UBE3B gene is involved in biological processes as a protein involved in the catabolic process of ubiquitin-dependent protein. NIF3L1 is involved in the biological process of neuronal differentiation, positive transcriptional regulation, DNA pattern, and negative transcriptional regulation by nucleic acid pattern. The ORC2 gene plays a role in the biological process of DNA replication. The genes KRT8, PHLDB3, PPT2, LOC787628, PPYR1, TOX, TP73, DHX8, KCNN1, CLEC6A, PXMP4, LRRC26, SLC34A3, and OR13C7 have been shown to be more highly expressed in the corpus luteum in low fertility cows. Among these genes, three genes PPT2, PPYR1 and CLEC6A were functional indicators. The loci UBE3B, NIF3L1 and ORC2, which were expressed more strongly in the corpus luteum of highly fertile cows, can be used as functional indicator genes in the genetic selection of dairy cows. [ABSTRACT FROM AUTHOR]

Background: Cells orchestrate histone biogenesis with strict temporal and quantitative control. To efficiently regulate histone biogenesis, the repetitive Drosophila melanogaster replication-dependent histone genes are arrayed and clustered at a single locus. Regulatory factors concentrate in a nuclear body known as the histone locus body (HLB), which forms around the locus. Historically, HLB factors are largely discovered by chance, and few are known to interact directly with DNA. It is therefore unclear how the histone genes are specifically targeted for unique and coordinated regulation. Results: To expand the list of known HLB factors, we performed a candidate-based screen by mapping 30 publicly available ChIP datasets of 27 unique factors to the Drosophila histone gene array. We identified novel transcription factor candidates, including the Drosophila Hox proteins Ultrabithorax (Ubx), Abdominal-A (Abd-A), and Abdominal-B (Abd-B), suggesting a new pathway for these factors in influencing body plan morphogenesis. Additionally, we identified six other factors that target the histone gene array: JIL-1, hormone-like receptor 78 (Hr78), the long isoform of female sterile homeotic (1) (fs(1)h) as well as the general transcription factors TBP associated factor 1 (TAF-1), Transcription Factor IIB (TFIIB), and Transcription Factor IIF (TFIIF). Conclusions: Our foundational screen provides several candidates for future studies into factors that may influence histone biogenesis. Further, our study emphasizes the powerful reservoir of publicly available datasets, which can be mined as a primary screening technique. [ABSTRACT FROM AUTHOR]

Background: 'Omics methods have empowered scientists to tackle the complexity of microbial communities on a scale not attainable before. Individually, omics analyses can provide great insight; while combined as "meta-omics", they enhance the understanding of which organisms occupy specific metabolic niches, how they interact, and how they utilize environmental nutrients. Here we present three integrative meta-omics workflows, developed in Galaxy, for enhanced analysis and integration of metagenomics, metatranscriptomics, and metaproteomics, combined with our newly developed web-application, ViMO (Visualizer for Meta-Omics) to analyse metabolisms in complex microbial communities. Results: In this study, we applied the workflows on a highly efficient cellulose-degrading minimal consortium enriched from a biogas reactor to analyse the key roles of uncultured microorganisms in complex biomass degradation processes. Metagenomic analysis recovered metagenome-assembled genomes (MAGs) for several constituent populations including Hungateiclostridium thermocellum, Thermoclostridium stercorarium and multiple heterogenic strains affiliated to Coprothermobacter proteolyticus. The metagenomics workflow was developed as two modules, one standard, and one optimized for improving the MAG quality in complex samples by implementing a combination of single- and co-assembly, and dereplication after binning. The exploration of the active pathways within the recovered MAGs can be visualized in ViMO, which also provides an overview of the MAG taxonomy and quality (contamination and completeness), and information about carbohydrate-active enzymes (CAZymes), as well as KEGG annotations and pathways, with counts and abundances at both mRNA and protein level. To achieve this, the metatranscriptomic reads and metaproteomic mass-spectrometry spectra are mapped onto predicted genes from the metagenome to analyse the functional potential of MAGs, as well as the actual expressed proteins and functions of the microbiome, all visualized in ViMO. Conclusion: Our three workflows for integrative meta-omics in combination with ViMO presents a progression in the analysis of 'omics data, particularly within Galaxy, but also beyond. The optimized metagenomics workflow allows for detailed reconstruction of microbial community consisting of MAGs with high quality, and thus improves analyses of the metabolism of the microbiome, using the metatranscriptomics and metaproteomics workflows. [ABSTRACT FROM AUTHOR]

Oort constants and local kinematics are vital parameters with which to study the structure and dynamics of the Milky Way. When GCNS was published, it provided a clean sample of stars in the solar vicinity, which gives us an ideal tool with which to determine these parameters. Our aim was to calculate the reliable Oort constants with GCNS. We determined the Oort constants using the GCNS from Gaia EDR3 with d < 100 pc . The proper motions and radial velocities were fitted with a maximum likelihood model. The uncertainties were obtained with an MCMC method. The sample was carefully selected to obtain a reliable result. The result yields the Oort constants A = 15.6 ± 1.6 km s − 1 kpc − 1 , B = − 15.8 ± 1.7 km s − 1 kpc − 1 , C = − 3.5 ± 1.6 km s − 1 kpc − 1 , and K = 2.7 ± 1.5 km s − 1 kpc − 1 . The non-zero C and K imply that the local disc is in a non-asymmetric potential. With the Oort constants, we derived the local angular velocity Ω 0 ≈ A − B = 31.4 ± 2.3 km s − 1 kpc − 1 . The solar motion ( U ⊙ , V ⊙ , W ⊙ ) was calculated as ( 10.1 ± 0.1 , 22.8 ± 0.1 , 7.8 ± 0.1 ) km s − 1 . [ABSTRACT FROM AUTHOR]

In this work, we investigate the possibility of observing quasars, particularly lensed quasars, by the Nancy Grace Roman Space Telescope (Roman). To this aim, based on the capabilities of the Roman Space Telescope and the results from the quasar luminosity function (QLF) in the infrared band of the Spitzer Space Telescope imaging survey, we calculated the number of quasars expected to be in its field of view. In order to estimate the number of lensed quasars, we develop a Monte Carlo simulation to estimate the probability that a quasar is lensed once or more times by foreground galaxies. Using the mass–luminosity distribution function of galaxies and the redshift distributions of galaxies and quasars, we find that 1 per 180 observed quasars will be lensed by foreground galaxies. Further on, adopting a singular isothermal sphere (SIS) model for lens galaxies, we calculate the time delay between lensed images for single and multiple lensing systems and present their distributions. We emphasize that detailed studies of these lensing systems will provide a powerful probe of the physical properties of quasars and may allow testing the mass distribution models of galaxies in addition to being extremely helpful for constraining the cosmological parameters. [ABSTRACT FROM AUTHOR]

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Can high-energy transient events affect life on a planet? We provide a review of the works that have tried to answer this question. It is argued that that gamma ray bursts, specifically those of the long class, are among the most dangerous astrophysical sources for biotic life and may exert evolutionary pressure on possible life forms in the universe. Their radiation can be directly lethal for biota or induce extinction by removing most of the protective atmospheric ozone layer on terrestrial planets. Since the rate of long gamma ray bursts is proportional to the birth rate of stars but is reduced in metal rich regions, the evolution of the "safest place" to live in our galaxy depended on the past 12 billion years of evolution of the star formation rate and relative metal pollution of the interstellar medium. Until 6 billion years ago, the outskirts of the galaxy were the safest places to live, despite the relatively low density of terrestrial planets. In the last 5 billion years, regions between 2 and 8 kiloparsecs from the center, featuring a higher density of terrestrial planets, gradually became the best places for safe biotic life growth. [ABSTRACT FROM AUTHOR]

In this study, the morphological galaxy classification process was carried out with a hybrid approach. Since the Galaxy classification process may contain detailed information about the universe's formation, it remains the current research topic. Researchers divided more than 100 billion galaxies into ten different classes. It is not always possible to understand which class the galaxy types belong. However, Artificial Intelligence (AI) can be used for successful classification. There are studies on the automatic classification of galaxies into a small number of classes. As the number of classes increases, the success of the used methods decreases. Based on the literature, the classification using Convolutional Neural Network (CNN) is better. Three metaheuristic algorithms are used to obtain the optimum architecture of CNN. These are Grey Wolf Optimizer (GWO), Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms. A CNN architecture with nine hidden layers and two full connected layers was used. The number of neurons in the hidden layers and the fully connected layers, the learning coefficient and the batch size values were optimized. The classification accuracy of my model was 85%. The best results were obtained usingGWO. Manual optimization of CNN is difficult. It was carried out with the help of the GWO meta-heuristic algorithm. [ABSTRACT FROM AUTHOR]

Plant genome-scale resources are being generated at an increasing rate as sequencing technologies continue to improve and raw data costs continue to fall; however, the cost of downstream analyses remains large. This has resulted in a considerable range of genome assembly and annotation qualities across plant genomes due to their varying sizes, complexity, and the technology used for the assembly and annotation. To effectively work across genomes, researchers increasingly rely on comparative genomic approaches that integrate across plant community resources and data types. Such efforts have aided the genome annotation process and yielded novel insights into the evolutionary history of genomes and gene families, including complex non-model organisms. The essential tools to achieve these insights rely on gene family analysis at a genome-scale, but they are not well integrated for rapid analysis of new data, and the learning curve can be steep. Here we present PlantTribes2, a scalable, easily accessible, highly customizable, and broadly applicable gene family analysis framework with multiple entry points including user provided data. It uses objective classifications of annotated protein sequences from existing, high-quality plant genomes for comparative and evolutionary studies. PlantTribes2 can improve transcript models and then sort them, either genome-scale annotations or individual gene coding sequences, into pre-computed orthologous gene family clusters with rich functional annotation information. Then, for gene families of interest, PlantTribes2 performs downstream analyses and customizable visualizations including, (1) multiple sequence alignment, (2) gene family phylogeny, (3) estimation of synonymous and non-synonymous substitution rates among homologous sequences, and (4) inference of large-scale duplication events. We give examples of PlantTribes2 applications in functional genomic studies of economically important plant families, namely transcriptomics in the weedy Orobanchaceae and a core orthogroup analysis (CROG) in Rosaceae. PlantTribes2 is freely available for use within the main public Galaxy instance and can be downloaded from GitHub or Bioconda. Importantly, PlantTribes2 can be readily adapted for use with genomic and transcriptomic data from any kind of organism. [ABSTRACT FROM AUTHOR]

Introduction: Antimicrobial susceptibility testing (AST) is used to determine the susceptibility of an organism to antibiotics. The determination of susceptibility is based on MIC breakpoints and is provided by EUCAST and CLSI. Likewise, phenotypic classification criteria developed by CDC/ECDC are used for the classification of pathogens into susceptible, multidrug-resistant, extremely drug-resistant, or totally drug-resistant categories. Wholegenome sequencing (WGS)-based diagnosis is now supplementing existing gold-standard microbiology methods for rapid and more precise AST, and therefore, EUCAST recommended quality criteria to assess whole-genome sequence for reporting the same. In this study, these three global standards, MIC breakpoints, phenotypic classification, and genome quality, are applied to the largest publicly available data for Acinetobacter baumannii (AB), the most critical priority pathogen identified by WHO. Materials and Methods: The drug sensitivity profile and genomes for isolates of AB were obtained from PATRIC and evaluated with respect to AST standards (CLSI and EUCAST). Whole genome quality assessment and antimicrobial resistance mapping is performed with QUAST and ABRicate, respectively. Four in-house methods are developed for mapping standards and are integrated into a Galaxy workflow based system, Galaxy-ASIST. Analysis of the extent of agreement between CLSI 2022 and EUCAST 2022 for antibiotics was carried out using Cohen’s kappa statistics. Results and Discussion: An automated pipeline, Galaxy-ASIST, is designed and developed for the characterization of clinical isolates based on these standards. Evaluation of over 6,500 AB strains using Galaxy-ASIST indicated that only 10% of the publicly available datasets have metadata to implement these standards. Furthermore, given that CLSI and EUCAST have different MIC breakpoints, discrepancies are observed in the classification of resistant and susceptible isolates following these standards. It is, therefore, imperative that platforms are developed that allow the evaluation of ever increasing phenotypic and genome sequence datasets for AST. Galaxy-ASIST offers a centralized repository and a structured metadata architecture to provide a single globally acceptable framework for AST profiling of clinical isolates based on global standards. The platform also offers subsequent fine mapping of antimicrobial-resistant determinants. [ABSTRACT FROM AUTHOR]

Background Hands-on training, whether in bioinformatics or other domains, often requires significant technical resources and knowledge to set up and run. Instructors must have access to powerful compute infrastructure that can support resource-intensive jobs running efficiently. Often this is achieved using a private server where there is no contention for the queue. However, this places a significant prerequisite knowledge or labor barrier for instructors, who must spend time coordinating deployment and management of compute resources. Furthermore, with the increase of virtual and hybrid teaching, where learners are located in separate physical locations, it is difficult to track student progress as efficiently as during in-person courses. Findings Originally developed by Galaxy Europe and the Gallantries project, together with the Galaxy community, we have created Training Infrastructure-as-a-Service (TIaaS), aimed at providing user-friendly training infrastructure to the global training community. TIaaS provides dedicated training resources for Galaxy-based courses and events. Event organizers register their course, after which trainees are transparently placed in a private queue on the compute infrastructure, which ensures jobs complete quickly, even when the main queue is experiencing high wait times. A built-in dashboard allows instructors to monitor student progress. Conclusions TIaaS provides a significant improvement for instructors and learners, as well as infrastructure administrators. The instructor dashboard makes remote events not only possible but also easy. Students experience continuity of learning, as all training happens on Galaxy, which they can continue to use after the event. In the past 60 months, 504 training events with over 24,000 learners have used this infrastructure for Galaxy training. [ABSTRACT FROM AUTHOR]

Gaia space mission of the European Space Agency was launched at the end of 2013 and will continue operations until 2025. The published data releases revolutionize the view of the Milky Way galaxy and beyond thanks to its unprecedented astrometry, photometry and spectroscopy. The paper reviews the products of the last data release of the Gaia mission and some of the scientific impacts of the data. We also discuss the future perspectives of Galaxy astrometry from space. [ABSTRACT FROM AUTHOR]

The use of whole-genome sequencing (WGS) for bacterial characterisation has increased substantially in the last decade. Its high throughput and decreasing cost have led to significant changes in outbreak investigations and surveillance of a wide variety of microbial pathogens. Despite the innumerable advantages of WGS, several drawbacks concerning data analysis and management, as well as a general lack of standardisation, hinder its integration in routine use. In this work, a bioinformatics workflow for (Illumina) WGS data is presented for bacterial characterisation including genome annotation, species identification, serotype prediction, antimicrobial resistance prediction, virulence-related genes and plasmid replicon detection, core-genome-based or single nucleotide polymorphism (SNP)-based phylogenetic clustering and sequence typing. Workflow was tested using a collection of 22 in-house sequences of Salmonella enterica isolates belonging to a local outbreak, coupled with a collection of 182 Salmonella genomes publicly available. No errors were reported during the execution period, and all genomes were analysed. The bioinformatics workflow can be tailored to other pathogens of interest and is freely available for academic and non-profit use as an uploadable file to the Galaxy platform. [ABSTRACT FROM AUTHOR]

Biological processes result from interactions among molecules and cell-to-cell communications. In the last 50 years, network theory has empowered advances in understanding molecular networks' structure and dynamics that regulate biological systems. Adopting a network data analysis point of view at more laboratories might enrich their research capacity to generate forward working hypotheses. This work briefly describes network theory origins and provides basic graph analysis principles in biological systems, specific centrality measurements, and the main models for network structures. Also, we describe a workflow employing user-friendly free platforms to process, construct, and analyze transcriptome data from a network perspective. With this assay, we expect to encourage the implementation of network theory analysis on biological data in everyday laboratory research. [ABSTRACT FROM AUTHOR]

Specimen Data Refinery (SDR) is a developing platform for automating transcription of specimens from natural history collections (Hardisty et al. 2022). SDR is based on computational workflows and digital twins using FAIR Digital Objects. We show our recent experiences with building SDR using the Galaxy workflow system and combining two FDO methodologies with open digital specimens (openDS) and RO-Crate data packaging. We suggest FDO improvements for incremental building of digital objects in computational workflows. [ABSTRACT FROM AUTHOR]

Detection of transients such as supernovae (SNe) and kilonovae (KNe) in early phase has recently become important for understanding the progenitor properties and multi-messenger astronomy. Predicting which galaxy has the higher probability of hosting the transient events would help detect the early phase of the events and get information on their progenitors. The SN and KN rates are known to be a function of star formation rate (SFR) and stellar mass of the host galaxy. The SFR of a galaxy can be estimated from ultraviolet (UV) luminosity. However, the UV magnitudes have been derived carefully only for a limited number of nearby galaxies. Here, we introduce GALEX galaxy catalog of all-sky UV brightness of low redshift galaxies. To do so, we derive the UV photometry of galaxies in the GLADE catalog using the GALEX AIS images, supplemented by GALEX NGS and MIS data. From the near-UV (NUV) and far-UV (FUV) magnitudes, we calculate the SFRs of the galaxies, which will further be useful for estimating the SN and KN rate. The results are compared with previous GALEX UV catalog of galaxies. There will be an updated catalog based on this catalog for calculating KN rate of the galaxies in the future work. [ABSTRACT FROM AUTHOR]

Gravity is so different from other fundamental forces that it is now essentially treated as a nonfundamental force of entropic origin. Several good studies have been carried out in this direction. Quantum gravity is a theory which combines gravity well with quantum physics. However, there are still many impediments to our understanding, especially in the limits of extreme. The effects of quantum gravity start appearing on the scene at Planck length which is the smallest length in nature idealized so far. Although this study incorporates a model which is valid for potential energy corrections at small distances, we have also given a bold try to use it consistently for the corrections at very large distances as well. The model uses two techniques, namely, Boltzmann and Tsallis statistical approaches to explore the thermodynamics within the ambit of the braneworld model giving its further modified version. We have computed the partition function by using both Boltzmann and Tsallis statistical approaches and then used it to study the thermodynamics of the braneworld model. We have analyzed both analytically and graphically, the thermodynamic quantities like Helmholtz free energy and specific heat. [ABSTRACT FROM AUTHOR]

The interest in gravitational waves (GW) has increased since the recent detections of such signals announced by the LIGO Scientific Collaboration and the Virgo Collaboration. On the other hand, also interesting is the study of the stochastic backgrounds of GW (SBGW), which could in principle be generated by a variety of sources and astrophysical processes; particularly, in the present paper we are concerned with the SBGW from MACHO binaries in the Galaxy. In our scheme, we take into account only MACHOs which are black holes (BHMACHOs) and are located up to 50 kpc from the center of the Galaxy. Our spectra, which are calculated in the scenarios with Ω h 2 = 0.1 and Ω h 2 = 1.0 , are parameterized by the fraction of the Galaxy’s dark halo mass which is in the form of BHMACHOs and are compared with some results found in the literature. Besides, we investigate in what situations the backgrounds are above the sensitivity curves of the Laser Interferometer Space Antenna (LISA), Einstein Telescope (ET), Advanced Virgo (AdV) and Advanced Laser Interferometer Gravitational-Wave Observatory Plus (LIGO A+). [ABSTRACT FROM AUTHOR]

The determination of the velocities, accelerations and the gravitational field intensity at a given location in a galaxy could potentially be achieved in an unexpected manner with the environment of the observer, for instance, the local mean mass density in the galaxy. This idea, mathematically supported by the asymmetric distance concept, is illustrated here by a study regarding the rotation of spiral galaxies. This suggestion is new in the astrophysics field (in the following, it is called the κ -model) and could help to mimic the main effects seen in modified Newtonian dynamics (MOND) theory, modified gravity (MOG) models, or other related models built with the aim of eliminating dark matter that are already well-established theories. Thus, starting from two selected examples of galaxies, in Sect. 5, we show that there is an equivalence between MOND and the κ -model. In particular, on the opposite side, we have the speculative nature of the dominant paradigm, the elusive dark matter, a matter whose properties always remain undefined despite intense theoretical, experimental and observational efforts for over 50 years. [ABSTRACT FROM AUTHOR]

Epitopes are portions of a protein that are recognized by antibodies. These small amino acid sequences represent a significant breakthrough in a branch of bioinformatics called immunoinformatics. Various software are available for linear B-cell epitope (BCE) prediction such as ABCPred, SVMTrip, EpiDope, and EpitopeVec ; a well-known BCE predictor is BepiPred-2.0. However, despite the prediction, there are several essential steps, such as epitope assembly, evaluation, and searching for epitopes in other proteomes. Here, we present EpiBuilder (https://epibuilder.sourceforge.io), a user friendly software that assists in epitope assembly, classifying and searching using input results of BepiPred-2.0. EpiBuilder generates several output results from these data and supports a proteome-wide processing approach. In addition, this software provides the following features: Chou & Fasman beta-turn prediction, Emini surface accessibility prediction, Karplus and Schulz flexibility prediction, Kolaskar and Tongaonkar antigenicity, Parker hydrophilicity prediction, N -glycosylation domains, and hydropathy. These information generate a unique topology for each epitope, visually demonstrating its characteristics. The software can search the entire epitope sequence in various FASTA files, and it allows to use BLASTP to identify epitopes that eventually have sequence variations. As an EpiBuilder application, we developed a epitope dataset from the protozoan Trypanosoma brucei gambiense, the gram-positive bacterium Clostridioides difficile, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). [ABSTRACT FROM AUTHOR]

Nucleosomes are basic units of DNA packing in eukaryotes. Their structure is well conserved from yeast to human and consists of the histone octamer core and 147 bp DNA wrapped around it. Nucleosomes are bound to a majority of the eukaryotic genomic DNA, including its regulatory regions. Hence, they also play a major role in gene regulation. For the latter, their precise positioning on DNA is essential. In the present paper, we describe Galaxy dnpatterntools—software package for nucleosome DNA sequence analysis and mapping. This software will be useful for computational biologists practitioners to conduct more profound studies of gene regulatory mechanisms. [ABSTRACT FROM AUTHOR]

An updated, binary-coded message has been developed for transmission to extraterrestrial intelligences in the Milky Way galaxy. The proposed message includes basic mathematical and physical concepts to establish a universal means of communication followed by information on the biochemical composition of life on Earth, the Solar System's time-stamped position in the Milky Way relative to known globular clusters, as well as digitized depictions of the Solar System, and Earth's surface. The message concludes with digitized images of the human form, along with an invitation for any receiving intelligences to respond. Calculation of the optimal timing during a given calendar year is specified for potential future transmission from both the Five-hundred-meter Aperture Spherical radio Telescope in China and the SETI Institute's Allen Telescope Array in northern California to a selected region of the Milky Way which has been proposed as the most likely location for life to have developed. These powerful new beacons, the successors to the Arecibo radio telescope which transmitted the 1974 message upon which this expanded communication is in part based, can carry forward Arecibo's legacy into the 21st century with this equally well-constructed communication from Earth's technological civilization. [ABSTRACT FROM AUTHOR]

Possible existence of antimatter in our Galaxy, in particular, of antistars is discussed and the mechanism of their creation is decribed. [ABSTRACT FROM AUTHOR]

Introduction: Breast cancer is the swelling structures in the breast cells. After skin cancer, breast cancer is the most broadly accepted malignancy analysed in ladies in the United States. Breast cancer can happen in both males and females, yet it's undeniably more normal in ladies. Indications of mammary glands cancer may involve a ball or lumps in the breast, an alteration of breast shape, scratching of the skin, fluid coming out from areola, a recently reversed areola, or a red or textured fix of skin. In those with removed lay out of the illness, there can be bone agony, swollen lymph hubs, windedness, or yellow skin. There are certain microorganisms that are involved in breast cancer and have function thereof. The study of these microorganisms can be done through metagenomics study and comparing with normal samples. Methods: For current study pairwise metagenomics data for breast cancer sample was retrieved from ENA site. Four FASTQ files were retrieved with the Accession no PRJEB25419 and complete metagenomics analysis was done using GALAXY Server. Tools like FASTQC, Trim galore, KRAKEN2, Krona pie chart etc. were used for classification and identification of microorganisms in the samples. Results: The taxonomic and functional analysis of the metagenome of breast cancer identifies different organisms like. Actinobacteria, Bifidobacterium cuniculi, Murnine leukemia virus, Human endogenous retrovirus, Pezizomycotina. Different microbes and their percentage in the breast cancer have been predicted that are 4% of Nematocera, 2% of Brachycera, 3% of Galegeae, 2% of Nelumbo nucifera. Conclusion These results give insights into the metagenome of breast cancer that can be used for clinical perspectives. Detailed study is required to establish the association of these microbes with development and progression of breast cancer. [ABSTRACT FROM AUTHOR]

We have studied the system of globular clusters (GCs) that formed in other galaxies and eventually accreted onto the Milky Way. Thus, the samples of GCs belonging to different tidal streams, obtained on the basis of the latest data from the GAIA observatory, were taken from the literature. We measured the anisotropy of the distribution of these GCs using the tensor of inertia and found that the distribution of GCs in the streams is isotropic. Nevertheless, it can be seen that some of the accreted GCs included into existing samples actually belong to the disk of the Galaxy. To clarify the origin of GCs, we investigated "the age–metallicity" relation. This dependence appeared to be bimodal and its two different branches clearly show the difference between the clusters formed in the streams and in the disk of the Galaxy. Furthermore, we have studied the influence of the large-scale environment of the Galaxy (i.e., the Local Supercluster) on the distribution of satellite galaxies and Galactic GCs. The satellite galaxies of the Milky Way are known to form an anisotropic planar structure, so we included them in our analysis too. An inspection has shown that the plane of the satellite galaxies is perpendicular both to the disk of the Galaxy and the supergalactic plane. For GCs more distant than 100 Kpc, a similar picture is observed. [ABSTRACT FROM AUTHOR]

Some important predictions from 4 main models of spiral arm formation are tested here, using observational data acquired for the Milky Way galaxy. Many spiral arm models (density wave, tidal wave, nuclear Lyapunov tube, or dynamic transient wave) have some consistencies with some of the observations, and some inconsistencies. Our 4 tests consist of the relative locations and relative speeds of different arm tracers away from the dust lane, and the global arm pitch angle as obtained over two Galactic quadrants and several Galactic radii, as well as the arm's continuity of shape from Galactic quadrant IV to Galactic quadrant I. In the Milky Way, an age gradient is observed from different arm tracers, amounting to 12.9 ± 1.1 Myrs/kpc, or a relative speed from the dust lane of 76 ± 10 km/s. The presence of an age gradient is predicted by the density waves, but is not consistent with the predictions of the tidal waves, of the nuclear Lyapunov tubes, nor of the dynamic transient recurrent waves. [ABSTRACT FROM AUTHOR]

The discipline of Information Systems is often viewed as a social science. Information Systems research and teaching pertain to the management and sociological issues of the computing field. It also includes programming and systems analysis, design and development. It is, therefore, challenging to plot Information Systems on a continuum of disciplinary clusters. Depending on the viewpoint held on the scientific world, the groups of disciplines take on different forms. Although metaphors are often used in Information Systems to portray complex ideas in understandable ways, only a few papers could be found that explain the interdisciplinary nature of the discipline metaphorically. To fill this gap, this article uses the astronomical concepts of galaxy, constellation and asterism to explain the place of Information Systems within the scientific domain. An asterism is a grouping of stars which may be part of various constellations. Six different Information Systems asterisms are proposed. The conceptual reflection in the article offers a fresh perspective on the interdisciplinary nature of Information Systems to the philosophy of science. The article illustrates the proposed metaphors with some existing examples to validate the concept. Suggestions for future research are also provided. [ABSTRACT FROM AUTHOR]

Background Data-independent acquisition (DIA) has become an important approach in global, mass spectrometric proteomic studies because it provides in-depth insights into the molecular variety of biological systems. However, DIA data analysis remains challenging owing to the high complexity and large data and sample size, which require specialized software and vast computing infrastructures. Most available open-source DIA software necessitates basic programming skills and covers only a fraction of a complete DIA data analysis. In consequence, DIA data analysis often requires usage of multiple software tools and compatibility thereof, severely limiting the usability and reproducibility. Findings To overcome this hurdle, we have integrated a suite of open-source DIA tools in the Galaxy framework for reproducible and version-controlled data processing. The DIA suite includes OpenSwath, PyProphet, diapysef, and swath2stats. We have compiled functional Galaxy pipelines for DIA processing, which provide a web-based graphical user interface to these pre-installed and pre-configured tools for their use on freely accessible, powerful computational resources of the Galaxy framework. This approach also enables seamless sharing workflows with full configuration in addition to sharing raw data and results. We demonstrate the usability of an all-in-one DIA pipeline in Galaxy by the analysis of a spike-in case study dataset. Additionally, extensive training material is provided to further increase access for the proteomics community. Conclusion The integration of an open-source DIA analysis suite in the web-based and user-friendly Galaxy framework in combination with extensive training material empowers a broad community of researches to perform reproducible and transparent DIA data analysis. [ABSTRACT FROM AUTHOR]

Epitopes are portions of a protein that are recognized by antibodies. These small amino acid sequences represent a significant breakthrough in a branch of bioinformatics called immunoinformatics. Various software are available for linear B-cell epitope (BCE) prediction such as ABCPred, SVMTrip, EpiDope, and EpitopeVec; a well-known BCE predictor is BepiPred-2.0. However, despite the prediction, there are several essential steps, such as epitope assembly, evaluation, and searching for epitopes in other proteomes. Here, we present EpiBuilder (https://epibuilder.sourceforge.io), a user friendly software that assists in epitope assembly, classifying and searching using input results of BepiPred-2.0. EpiBuilder generates several output results from these data and supports a proteome-wide processing approach. In addition, this software provides the following features: Chou & Fasman beta-turn prediction, Emini surface accessibility prediction, Karplus and Schulz flexibility prediction, Kolaskar and Tongaonkar antigenicity, Parker hydrophilicity prediction, N-glycosylation domains, and hydropathy. These information generate a unique topology for each epitope, visually demonstrating its characteristics. The software can search the entire epitope sequence in various FASTA files, and it allows to use BLASTP to identify epitopes that eventually have sequence variations. As an EpiBuilder application, we developed a epitope dataset from the protozoan Trypanosoma brucei gambiense, the gram-positive bacterium Clostridioides difficile, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). [ABSTRACT FROM AUTHOR]

Background: Improving the availability and usability of data and analytical tools is a critical precondition for further advancing modern biological and biomedical research. For instance, one of the many ramifications of the COVID-19 global pandemic has been to make even more evident the importance of having bioinformatics tools and data readily actionable by researchers through convenient access points and supported by adequate IT infrastructures. One of the most successful efforts in improving the availability and usability of bioinformatics tools and data is represented by the Galaxy workflow manager and its thriving community. In 2020 we introduced Laniakea, a software platform conceived to streamline the configuration and deployment of "on-demand" Galaxy instances over the cloud. By facilitating the set-up and configuration of Galaxy web servers, Laniakea provides researchers with a powerful and highly customisable platform for executing complex bioinformatics analyses. The system can be accessed through a dedicated and user-friendly web interface that allows the Galaxy web server's initial configuration and deployment. Results: "Laniakea@ReCaS", the first instance of a Laniakea-based service, is managed by ELIXIR-IT and was officially launched in February 2020, after about one year of development and testing that involved several users. Researchers can request access to Laniakea@ReCaS through an open-ended call for use-cases. Ten project proposals have been accepted since then, totalling 18 Galaxy on-demand virtual servers that employ ~ 100 CPUs, ~ 250 GB of RAM and ~ 5 TB of storage and serve several different communities and purposes. Herein, we present eight use cases demonstrating the versatility of the platform. Conclusions: During this first year of activity, the Laniakea-based service emerged as a flexible platform that facilitated the rapid development of bioinformatics tools, the efficient delivery of training activities, and the provision of public bioinformatics services in different settings, including food safety and clinical research. Laniakea@ReCaS provides a proof of concept of how enabling access to appropriate, reliable IT resources and ready-to-use bioinformatics tools can considerably streamline researchers' work. [ABSTRACT FROM AUTHOR]