Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries.
- MeSH
- Computational Biology * education MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Extramural MeSH
- Geographicals
- Nigeria MeSH
The corpus of bioinformatics resources is huge and expanding rapidly, presenting life scientists with a growing challenge in selecting tools that fit the desired purpose. To address this, the European Infrastructure for Biological Information is supporting a systematic approach towards a comprehensive registry of tools and databases for all domains of bioinformatics, provided under a single portal (https://bio.tools). We describe here the practical means by which scientific communities, including individual developers and projects, through major service providers and research infrastructures, can describe their own bioinformatics resources and share these via bio.tools.
- Keywords
- bioinformatics, community driven, curation, database, registry, software,
- MeSH
- Humans MeSH
- Software * MeSH
- Database Management Systems MeSH
- Community Participation * MeSH
- Computational Biology methods standards MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
Several new viral infections have emerged in the human population and establishing as global pandemics. With advancements in translation research, the scientific community has developed potential therapeutics to eradicate or control certain viral infections, such as smallpox and polio, responsible for billions of disabilities and deaths in the past. Unfortunately, some viral infections, such as dengue virus (DENV) and human immunodeficiency virus-1 (HIV-1), are still prevailing due to a lack of specific therapeutics, while new pathogenic viral strains or variants are emerging because of high genetic recombination or cross-species transmission. Consequently, to combat the emerging viral infections, bioinformatics-based potential strategies have been developed for viral characterization and developing new effective therapeutics for their eradication or management. This review attempts to provide a single platform for the available wide range of bioinformatics-based approaches, including bioinformatics methods for the identification and management of emerging or evolved viral strains, genome analysis concerning the pathogenicity and epidemiological analysis, computational methods for designing the viral therapeutics, and consolidated information in the form of databases against the known pathogenic viruses. This enriched review of the generally applicable viral informatics approaches aims to provide an overview of available resources capable of carrying out the desired task and may be utilized to expand additional strategies to improve the quality of translation viral informatics research.
- Keywords
- artificial intelligence, drug discovery, vaccine development, viral informatics, viral pandemic,
- MeSH
- Humans MeSH
- Pandemics MeSH
- Virus Diseases * drug therapy genetics MeSH
- Computational Biology * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
Structural bioinformatics provides the scientific methods and tools to analyse, archive, validate, and present the biomolecular structure data generated by the structural biology community. It also provides an important link with the genomics community, as structural bioinformaticians also use the extensive sequence data to predict protein structures and their functional sites. A very broad and active community of structural bioinformaticians exists across Europe, and 3D-Bioinfo will establish formal platforms to address their needs and better integrate their activities and initiatives. Our mission will be to strengthen the ties with the structural biology research communities in Europe covering life sciences, as well as chemistry and physics and to bridge the gap between these researchers in order to fully realize the potential of structural bioinformatics. Our Community will also undertake dedicated educational, training and outreach efforts to facilitate this, bringing new insights and thus facilitating the development of much needed innovative applications e.g. for human health, drug and protein design. Our combined efforts will be of critical importance to keep the European research efforts competitive in this respect. Here we highlight the major European contributions to the field of structural bioinformatics, the most pressing challenges remaining and how Europe-wide interactions, enabled by ELIXIR and its platforms, will help in addressing these challenges and in coordinating structural bioinformatics resources across Europe. In particular, we present recent activities and future plans to consolidate an ELIXIR 3D-Bioinfo Community in structural bioinformatics and propose means to develop better links across the community. These include building new consortia, organising workshops to establish data standards and seeking community agreement on benchmark data sets and strategies. We also highlight existing and planned collaborations with other ELIXIR Communities and other European infrastructures, such as the structural biology community supported by Instruct-ERIC, with whom we have synergies and overlapping common interests.
- Keywords
- ELIXIR, Instruct-ERIC, biomolecular structure, nucleic acids structure, protein structure, structural bioinformatics,
- MeSH
- Biological Science Disciplines * MeSH
- Genomics MeSH
- Humans MeSH
- Proteins MeSH
- Computational Biology organization & administration MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
- Names of Substances
- Proteins MeSH
Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.
Environmental DNA (eDNA) metabarcoding has gained growing attention as a strategy for monitoring biodiversity in ecology. However, taxa identifications produced through metabarcoding require sophisticated processing of high-throughput sequencing data from taxonomically informative DNA barcodes. Various sets of universal and taxon-specific primers have been developed, extending the usability of metabarcoding across archaea, bacteria and eukaryotes. Accordingly, a multitude of metabarcoding data analysis tools and pipelines have also been developed. Often, several developed workflows are designed to process the same amplicon sequencing data, making it somewhat puzzling to choose one among the plethora of existing pipelines. However, each pipeline has its own specific philosophy, strengths and limitations, which should be considered depending on the aims of any specific study, as well as the bioinformatics expertise of the user. In this review, we outline the input data requirements, supported operating systems and particular attributes of thirty-two amplicon processing pipelines with the goal of helping users to select a pipeline for their metabarcoding projects.
- Keywords
- amplicon data analysis, bioinformatics, environmental DNA, metabarcoding, pipeline, review,
- MeSH
- Data Analysis MeSH
- Archaea genetics classification MeSH
- Bacteria genetics classification MeSH
- DNA, Environmental genetics MeSH
- Eukaryota genetics classification MeSH
- Metagenomics methods MeSH
- Software * MeSH
- DNA Barcoding, Taxonomic * methods MeSH
- Computational Biology * methods MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
- Names of Substances
- DNA, Environmental MeSH
Protein engineering strategies aimed at constructing enzymes with novel or improved activities, specificities, and stabilities greatly benefit from in silico methods. Computational methods can be principally grouped into three main categories: bioinformatics; molecular modelling; and de novo design. Particularly de novo protein design is experiencing rapid development, resulting in more robust and reliable predictions. A recent trend in the field is to combine several computational approaches in an interactive manner and to complement them with structural analysis and directed evolution. A detailed investigation of designed catalysts provides valuable information on the structural basis of molecular recognition, biochemical catalysis, and natural protein evolution.
- MeSH
- Enzymes genetics MeSH
- Humans MeSH
- Models, Molecular MeSH
- Mutation MeSH
- Protein Engineering methods MeSH
- Enzyme Stability MeSH
- Computational Biology methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Review MeSH
- Names of Substances
- Enzymes MeSH
ELIXIR is a pan-European intergovernmental organisation for life science that aims to coordinate bioinformatics resources in a single infrastructure across Europe; bioinformatics training is central to its strategy, which aims to develop a training community that spans all ELIXIR member states. In an evidence-based approach for strengthening bioinformatics training programmes across Europe, the ELIXIR Training Platform, led by the ELIXIR EXCELERATE Quality and Impact Assessment Subtask in collaboration with the ELIXIR Training Coordinators Group, has implemented an assessment strategy to measure quality and impact of its entire training portfolio. Here, we present ELIXIR's framework for assessing training quality and impact, which includes the following: specifying assessment aims, determining what data to collect in order to address these aims, and our strategy for centralised data collection to allow for ELIXIR-wide analyses. In addition, we present an overview of the ELIXIR training data collected over the past 4 years. We highlight the importance of a coordinated and consistent data collection approach and the relevance of defining specific metrics and answer scales for consortium-wide analyses as well as for comparison of data across iterations of the same course.
- MeSH
- Algorithms MeSH
- Biomedical Research MeSH
- Databases, Factual MeSH
- Program Evaluation MeSH
- Education, Continuing MeSH
- Curriculum MeSH
- Reproducibility of Results MeSH
- Quality Control * MeSH
- Data Collection MeSH
- Software MeSH
- User-Computer Interface MeSH
- Computational Biology education standards MeSH
- Research Personnel MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Europe MeSH
The molecular recognition of carbohydrates by proteins plays a key role in many biological processes including immune response, pathogen entry into a cell, and cell-cell adhesion (e.g., in cancer metastasis). Carbohydrates interact with proteins mainly through hydrogen bonding, metal-ion-mediated interaction, and non-polar dispersion interactions. The role of dispersion-driven CH-π interactions (stacking) in protein-carbohydrate recognition has been underestimated for a long time considering the polar interactions to be the main forces for saccharide interactions. However, over the last few years it turns out that non-polar interactions are equally important. In this study, we analyzed the CH-π interactions employing bioinformatics (data mining, structural analysis), several experimental (isothermal titration calorimetry (ITC), X-ray crystallography), and computational techniques. The Protein Data Bank (PDB) has been used as a source of structural data. The PDB contains over 12 000 protein complexes with carbohydrates. Stacking interactions are very frequently present in such complexes (about 39 % of identified structures). The calculations and the ITC measurement results suggest that the CH-π stacking contribution to the overall binding energy ranges from 4 up to 8 kcal mol-1 . All the results show that the stacking CH-π interactions in protein-carbohydrate complexes can be considered to be a driving force of the binding in such complexes.
- Keywords
- carbohydrates, density functional calculations, glycosylation, ligand binding, stacking interaction,
- MeSH
- Proteins chemistry MeSH
- Carbohydrates chemistry MeSH
- In Vitro Techniques MeSH
- Thermodynamics MeSH
- Carbon chemistry MeSH
- Protein Binding MeSH
- Hydrogen chemistry MeSH
- Hydrogen Bonding MeSH
- Computational Biology * MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Proteins MeSH
- Carbohydrates MeSH
- Carbon MeSH
- Hydrogen MeSH
BACKGROUND: Long non-coding RNAs (lncRNAs) as an important fraction of human transcriptome have been shown to exert fundamental role in regulation of signaling pathways implicated in carcinogenesis. Among them is vitamin D receptor (VDR) signaling whose participation in various cancers including breast cancer (BC) is evident. In spite of the presence of several evidences for participation of lncRNAs as well as VDR signaling in BC pathogenesis, no comprehensive study has evaluated the link between lncRNA dysregulation and VDR signaling in BC. AIM: To introduce a bioinformatics approach for identification of lncRNAs that modulate VDR signaling in BC. This approach includes co-expression analysis, in silico identification of lncRNAs that target VDR and literature search. CONCLUSIONS: Tens of lncRNAs are predicted to affect VDR signaling. Among them are some lncRNAs such as MALAT1 which has prominent role in BC pathogenesis. Identification of the lncRNAs that influence VDR gene expression is possible through in silico analysis. Considering the prominent role of VDR in BC pathogenesis as well as availability of VDR modulating agents, evaluation of VDR signaling pathway and related networks are of practical significance and bioinformatics tools are expected to facilitate such action. Key words: vitamin D receptor - long non-coding RNAs - co-expression - bioinformatics - calcitriol receptor - computational biology.
- Keywords
- vitamin D receptor - long non-coding RNAs - co-expression - bioinformatics - calcitriol receptor - computational biology,
- MeSH
- Humans MeSH
- Breast Neoplasms genetics metabolism MeSH
- Receptors, Calcitriol metabolism MeSH
- RNA, Long Noncoding metabolism MeSH
- Signal Transduction MeSH
- Computational Biology MeSH
- Check Tag
- Humans MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Receptors, Calcitriol MeSH
- RNA, Long Noncoding MeSH
- VDR protein, human MeSH Browser
