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Abstract

Fungi have crucial roles in ecosystems, and are important associates for many organisms. They are adapted to a wide variety of habitats, however their global distribution and diversity remains poorly documented. The exponential growth of DNA barcode information retrieved from the environment is assisting considerably the traditional ways for unraveling fungal diversity and detection. The raw DNA data in association to environmental descriptors of metabarcoding studies are made available in public sequence read archives. While this is potentially a valuable source of information for the investigation of Fungi across diverse environmental conditions, the annotation used to describe environment is heterogenous. Moreover, a uniform processing pipeline still needs to be applied to the available raw DNA data. Hence, a comprehensive framework to analyses these data in a large context is still lacking. We introduce the MycoDiversity DataBase, a database which includes public fungal metabarcoding data of environmental samples for the study of biodiversity patterns of Fungi. The framework we propose will contribute to our understanding of fungal biodiversity and aims to become a valuable source for large-scale analyses of patterns in space and time, in addition to assisting evolutionary and ecological research on Fungi.

Abstract

In the field of computational biology, in order to simulate multiscale biological systems, the Cellular Potts Model (CPM) has been used, which determines the actions that simulated cells can perform by determining a hamiltonian of energy that takes into account the influence that neighboring cells exert, under a wide range of parameters. There are some proposals in the literature that parallelize the CPM; in all cases, either lock-based techniques or other techniques that require large amounts of information to be disseminated among parallel tasks are used to preserve data coherence. In both cases, computational performance is limited. This work proposes an alternative approach for the parallelization of the model that uses transactional memory to maintain the coherence of the information. A Java implementation has been applied to the simulation of the ductal adenocarcinoma of breast in situ (DCIS). Times and speedups of the simulated execution of the model on the cluster of our university are analyzed. The results show a good speedup.

Abstract

Prochlorococcus marinus MIT 9303 is a marine cyanobacterium found in sea waters. It was first isolated from a depth of 100 m in the Sargasso Sea in the year 1992. This cyanobacterium serves as a good model system for scientific research due to the presence of many desirable characteristics like smaller in size, ability to perform photosynthesis and the ease of culture maintenance. The genome of this cyanobacterium encodes for about 3022 proteins. Out of these 3022 proteins, few proteins were annotated as hypothetical proteins. We performed a computational study to characterize one of the hypothetical proteins “P9303_05031” to deduce its functional role in the cell using various bioinformatics techniques. After in-depth analysis, this hypothetical protein showed the conserved domain as of Hsp10 of molecular chaperonins of GroES. In this work, we have predicted the bidirectional best hits for the hypothetical protein P9303_05031 followed by the prediction of protein properties such as primary, secondary and tertiary structures. The existence of the Hsp10 domain indicates its role is essential for the folding of proteins during heat shock. This work represents the first structural and physicochemical study of the hypothetical protein P9303_05031 in Prochlorococcus marinus MIT 9303.

Abstract

JIB.tools 2.0 is a new approach to more closely embed the curation process in the publication process. This website hosts the tools, software applications, databases and workflow systems published in the Journal of Integrative Bioinformatics (JIB). As soon as a new tool-related publication is published in JIB, the tool is posted to JIB.tools and can afterwards be easily transferred to bio.tools, a large information repository of software tools, databases and services for bioinformatics and the life sciences. In this way, an easily-accessible list of tools is provided which were published in JIB a well as status information regarding the underlying service. With newer registries like bio.tools providing these information on a bigger scale, JIB.tools 2.0 closes the gap between journal publications and registry publication. (Reference: https://jib.tools).

Abstract

The infection mechanism and pathogenicity of Human T-lymphotropic virus 1 (HTLV-1) are ambiguously known for hundreds of years. Our knowledge about this virus is recently emerging. The purpose of the study is to design a vaccine targeting the envelope glycoprotein, GP62, an outer membrane protein of HTLV-1 that has an increased number of epitope binding sites. Data collection, clustering and multiple sequence alignment of HTLV-1 glycoprotein B, variability analysis of envelope Glycoprotein GP62 of HTLV-1, population protection coverage, HLA-epitope binding prediction, and B-cell epitope prediction were performed to predict an effective vaccine. Among all the predicted peptides, ALQTGITLV and VPSSSTPL epitopes interact with three MHC alleles. The summative population protection coverage worldwide by these epitopes as vaccine candidates was found nearly 70%. The docking analysis revealed that ALQTGITLV and VPSSSTPL epitopes interact strongly with the epitope-binding groove of HLA-A*02:03, and HLA-B*35:01, respectively, as this HLA molecule was found common with which every predicted epitope interacts. Molecular dynamics simulations of the docked complexes show they form stable complexes. So, these potential epitopes might pave the way for vaccine development against HTLV-1.

Abstract

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.

Abstract

In this article, we propose a semi-automated method to rebuild genome ancestors of chloroplasts by taking into account gene duplication. Two methods have been used in order to achieve this work: a naked eye investigation using homemade scripts, whose results are considered as a basis of knowledge, and a dynamic programming based approach similar to Needleman-Wunsch. The latter fundamentally uses the Gestalt pattern matching method of sequence matcher to evaluate the occurrences probability of each gene in the last common ancestor of two given genomes. The two approaches have been applied on chloroplastic genomes from Apiales, Asterales, and Fabids orders, the latter belonging to Pentapetalae group. We found that Apiales species do not undergo indels, while they occur in the Asterales and Fabids orders. A series of experiments was then carried out to extensively verify our findings by comparing the obtained ancestral reconstruction results with the latest released approach called MLGO (Maximum Likelihood for Gene-Order analysis).

Abstract

For more than one decade, CELLmicrocosmos tools are being developed. Here, we discus some of the technical and administrative hurdles to keep a software suite running so many years. The tools were being developed during a number of student projects and theses, whereas main developers refactored and maintained the code over the years. The focus of this publication is laid on two Java-based Open Source Software frameworks. Firstly, the CellExplorer with the PathwayIntegration combines the mesoscopic and the functional level by mapping biological networks onto cell components using database integration. Secondly, the MembraneEditor enables users to generate membranes of different lipid and protein compositions using the PDB format. Technicalities will be discussed as well as the historical development of these tools with a special focus on group-based development. In this way, university-associated developers of Integrative Bioinformatics applications should be inspired to go similar ways. All tools discussed in this publication can be downloaded and installed from https://www.CELLmicrocosmos.org.