Biological databases are libraries of biological sciences, collected from scientific experiments, published literature, high-throughput experiment technology, and computational analysis. They contain information from research areas including genomics, proteomics, metabolomics, microarray gene expression, and phylogenetics. Information contained in biological databases includes gene function, structure, localization, clinical effects of mutations as well as similarities of biological sequences and structures.
In academia, computational immunology is a field of science that encompasses high-throughput genomic and bioinformatics approaches to immunology. The field's main aim is to convert immunological data into computational problems, solve these problems using mathematical and computational approaches and then convert these results into immunologically meaningful interpretations.
Pfam is a database of protein families that includes their annotations and multiple sequence alignments generated using hidden Markov models. The most recent version, Pfam 36.0, was released in September 2023 and contains 20,795 families.
The Biological General Repository for Interaction Datasets (BioGRID) is a curated biological database of protein-protein interactions, genetic interactions, chemical interactions, and post-translational modifications created in 2003 (originally referred to as simply the General Repository for Interaction Datasets by Mike Tyers, Bobby-Joe Breitkreutz, and Chris Stark at the Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital. It strives to provide a comprehensive curated resource for all major model organism species while attempting to remove redundancy to create a single mapping of data. Users of The BioGRID can search for their protein, chemical or publication of interest and retrieve annotation, as well as curated data as reported, by the primary literature and compiled by in house large-scale curation efforts. The BioGRID is hosted in Toronto, Ontario, Canada and Dallas, Texas, United States and is partnered with the Saccharomyces Genome Database, FlyBase, WormBase, PomBase, and the Alliance of Genome Resources. The BioGRID is funded by the NIH and CIHR. BioGRID is an observer member of the International Molecular Exchange Consortium.
Mouse Genome Informatics (MGI) is a free, online database and bioinformatics resource hosted by The Jackson Laboratory, with funding by the National Human Genome Research Institute (NHGRI), the National Cancer Institute (NCI), and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). MGI provides access to data on the genetics, genomics and biology of the laboratory mouse to facilitate the study of human health and disease. The database integrates multiple projects, with the two largest contributions coming from the Mouse Genome Database and Mouse Gene Expression Database (GXD). As of 2018, MGI contains data curated from over 230,000 publications.
The Reference Sequence (RefSeq) database is an open access, annotated and curated collection of publicly available nucleotide sequences and their protein products. RefSeq was introduced in 2000. This database is built by National Center for Biotechnology Information (NCBI), and, unlike GenBank, provides only a single record for each natural biological molecule for major organisms ranging from viruses to bacteria to eukaryotes.
In molecular biology, STRING is a biological database and web resource of known and predicted protein–protein interactions.
Pathogenomics is a field which uses high-throughput screening technology and bioinformatics to study encoded microbe resistance, as well as virulence factors (VFs), which enable a microorganism to infect a host and possibly cause disease. This includes studying genomes of pathogens which cannot be cultured outside of a host. In the past, researchers and medical professionals found it difficult to study and understand pathogenic traits of infectious organisms. With newer technology, pathogen genomes can be identified and sequenced in a much shorter time and at a lower cost, thus improving the ability to diagnose, treat, and even predict and prevent pathogenic infections and disease. It has also allowed researchers to better understand genome evolution events - gene loss, gain, duplication, rearrangement - and how those events impact pathogen resistance and ability to cause disease. This influx of information has created a need for bioinformatics tools and databases to analyze and make the vast amounts of data accessible to researchers, and it has raised ethical questions about the wisdom of reconstructing previously extinct and deadly pathogens in order to better understand virulence.
Bacterial small RNAs (bsRNA) are small RNAs produced by bacteria; they are 50- to 500-nucleotide non-coding RNA molecules, highly structured and containing several stem-loops. Numerous sRNAs have been identified using both computational analysis and laboratory-based techniques such as Northern blotting, microarrays and RNA-Seq in a number of bacterial species including Escherichia coli, the model pathogen Salmonella, the nitrogen-fixing alphaproteobacterium Sinorhizobium meliloti, marine cyanobacteria, Francisella tularensis, Streptococcus pyogenes, the pathogen Staphylococcus aureus, and the plant pathogen Xanthomonas oryzae pathovar oryzae. Bacterial sRNAs affect how genes are expressed within bacterial cells via interaction with mRNA or protein, and thus can affect a variety of bacterial functions like metabolism, virulence, environmental stress response, and structure.
PATRIC was a bacterial bioinformatics website from the Bioinformatics Resource Center, originally created in 2004. It has since been combined with the Influenza Research Database and the Virus Pathogen Database and Analysis Resource Center to create the Bacterial and Viral Bioinformatics Resource Center (BV-BRC). It is an information system that integrates databases and analysis tools. Its focus is on various data related to bacterial pathogens. PATRIC facilitates integration of various types of pathogen information to support biomedical research on bacterial infectious diseases.
This microRNA database and microRNA targets databases is a compilation of databases and web portals and servers used for microRNAs and their targets. MicroRNAs (miRNAs) represent an important class of small non-coding RNAs (ncRNAs) that regulate gene expression by targeting messenger RNAs.
PDBsum is a database that provides an overview of the contents of each 3D macromolecular structure deposited in the Protein Data Bank (PDB).
The Vaccine Investigation and OnLine Information Network (VIOLIN) is the largest web-based vaccine database and analysis system. VIOLIN currently contains over 3,000 vaccines or vaccine candidates for over 190 pathogens. The vaccine information in the database is collected by manual curation from over 1,600 peer-reviewed papers. Different from most existing vaccine databases, VIOLIN focuses on vaccine research data. Different types of information is curated, including vaccine name, license status, antigens used, vaccine adjuvants, vaccine vectors, vaccination procedure, host immune response, challenge procedure, vaccine efficacy, adverse events, etc. All vaccine information in the VIOLIN vaccine database is supported by quoted references. The data generated by a curator is published only after a careful review and approval by a vaccine domain expert.
PhytoPath was a joint scientific project between the European Bioinformatics Institute and Rothamsted Research, running from January 2012 to May 30, 2017. The project aimed to enable the exploitation of the growing body of “-omics” data being generated for phytopathogens, their plant hosts and related model species. Gene mutant phenotypic information is directly displayed in genome browsers.
PomBase is a model organism database that provides online access to the fission yeast Schizosaccharomyces pombe genome sequence and annotated features, together with a wide range of manually curated functional gene-specific data. The PomBase website was redeveloped in 2016 to provide users with a more fully integrated, better-performing service.
Model organism databases (MODs) are biological databases, or knowledgebases, dedicated to the provision of in-depth biological data for intensively studied model organisms. MODs allow researchers to easily find background information on large sets of genes, plan experiments efficiently, combine their data with existing knowledge, and construct novel hypotheses. They allow users to analyse results and interpret datasets, and the data they generate are increasingly used to describe less well studied species. Where possible, MODs share common approaches to collect and represent biological information. For example, all MODs use the Gene Ontology (GO) to describe functions, processes and cellular locations of specific gene products. Projects also exist to enable software sharing for curation, visualization and querying between different MODs. Organismal diversity and varying user requirements however mean that MODs are often required to customize capture, display, and provision of data.
Donna R. Maglott is a staff scientist at the National Center for Biotechnology Information known for her research on large-scale genomics projects, including the mouse genome and development of databases required for genomics research.
The Monarch Initiative is a large scale bioinformatics web resource focused on leveraging existing biomedical knowledge to connect genotypes with phenotypes in an effort to aid research that combats genetic diseases. Monarch does this by integrating multi-species genotype, phenotype, genetic variant and disease knowledge from various existing biomedical data resources into a centralized and structured database. While this integration process has been traditionally done manually by basic researchers and clinicians on a case-by-case basis, The Monarch Initiative provides an aggregated and structured collection of data and tools that make biomedical knowledge exploration more efficient and effective.
Biocuration is the field of life sciences dedicated to organizing biomedical data, information and knowledge into structured formats, such as spreadsheets, tables and knowledge graphs. The biocuration of biomedical knowledge is made possible by the cooperative work of biocurators, software developers and bioinformaticians and is at the base of the work of biological databases.
