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.
Online Mendelian Inheritance in Man (OMIM) is a continuously updated catalog of human genes and genetic disorders and traits, with a particular focus on the gene-phenotype relationship. As of 28 June 2019, approximately 9,000 of the over 25,000 entries in OMIM represented phenotypes; the rest represented genes, many of which were related to known phenotypes.
The Gene Ontology (GO) is a major bioinformatics initiative to unify the representation of gene and gene product attributes across all species. More specifically, the project aims to: 1) maintain and develop its controlled vocabulary of gene and gene product attributes; 2) annotate genes and gene products, and assimilate and disseminate annotation data; and 3) provide tools for easy access to all aspects of the data provided by the project, and to enable functional interpretation of experimental data using the GO, for example via enrichment analysis. GO is part of a larger classification effort, the Open Biomedical Ontologies, being one of the Initial Candidate Members of the OBO Foundry.
The Rat Genome Database (RGD) is a database of rat genomics, genetics, physiology and functional data, as well as data for comparative genomics between rat, human and mouse. RGD is responsible for attaching biological information to the rat genome via structured vocabulary, or ontology, annotations assigned to genes and quantitative trait loci (QTL), and for consolidating rat strain data and making it available to the research community. RGD is working with groups such as the Programs for Genomic Applications at MCW and the National BioResource Project for the Rat (NBPR-Rat) in Japan to collect and make available comprehensive physiologic data for a variety of rat strains. They are also developing a suite of tools for mining and analyzing genomic, physiologic and functional data for the rat, and comparative data for rat, mouse and human.
The Open Biological and Biomedical Ontologies (OBO) Foundry is a group of people dedicated to build and maintain ontologies related to the life sciences,. The OBO Foundry establishes a set of principles for ontology development for creating a suite of interoperable reference ontologies in the biomedical domain. Currently, there are more than a hundred ontologies that follow the OBO Foundry principles.
The Generic Model Organism Database (GMOD) project provides biological research communities with a toolkit of open-source software components for visualizing, annotating, managing, and storing biological data. The GMOD project is funded by the United States National Institutes of Health, National Science Foundation and the USDA Agricultural Research Service.
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 Zebrafish Information Network is an online biological database of information about the zebrafish. The zebrafish is a widely used model organism for genetic, genomic, and developmental studies, and ZFIN provides an integrated interface for querying and displaying the large volume of data generated by this research. To facilitate use of the zebrafish as a model of human biology, ZFIN links these data to corresponding information about other model organisms and to human disease databases. Abundant links to external sequence databases and to genome browsers are included. Gene product, gene expression, and phenotype data are annotated with terms from biomedical ontologies. ZFIN is based at the University of Oregon in the United States, with funding provided by the National Institutes of Health (NIH).
Genotype to Phenotype Databases: a Holistic Approach (GEN2PHEN) is a European project aiming to develop a knowledge web portal integrating information from the genotype to the phenotype in a unifying portal: The Knowledge Centre].
The Disease Ontology (DO) is a formal ontology of human disease. The Disease Ontology project is hosted at the Institute for Genome Sciences at the University of Maryland School of Medicine.
Uberon is a comparative anatomy ontology representing a variety of structures found in animals, such as lungs, muscles, bones, feathers and fins. These structures are connected to other structures via relationships such as part-of and develops-from. One of the uses of this ontology is to integrate data from different biological databases, and other species-specific ontologies such as the Foundational Model of Anatomy.
The International Mouse Phenotyping Consortium (IMPC) is an international scientific endeavour to create and characterize the phenotype of 20,000 knockout mouse strains. Launched in September 2011, the consortium consists of over 15 research institutes across four continents with funding provided by the NIH, European national governments and the partner institutions.
The Human Phenotype Ontology (HPO) is a formal ontology of human phenotypes. Developed in collaboration with members of the Open Biomedical Ontologies Foundry, HPO currently contains over 13,000 terms and over 156,000 annotations to hereditary diseases. Data from Online Mendelian Inheritance in Man and medical literature were used to generate the terms currently in the HPO. The ontology contains over 50,000 annotations between phenotypes and hereditary disease.
Experimental factor ontology, also known as EFO, is an open-access ontology of experimental variables particularly those used in molecular biology. The ontology covers variables which include aspects of disease, anatomy, cell type, cell lines, chemical compounds and assay information. EFO is developed and maintained at the EMBL-EBI as a cross-cutting resource for the purposes of curation, querying and data integration in resources such as Ensembl, ChEMBL and Expression Atlas.
In bioinformatics, a Gene Disease Database is a systematized collection of data, typically structured to model aspects of reality, in a way to comprehend the underlying mechanisms of complex diseases, by understanding multiple composite interactions between phenotype-genotype relationships and gene-disease mechanisms. Gene Disease Databases integrate human gene-disease associations from various expert curated databases and text mining derived associations including Mendelian, complex and environmental diseases.
DisGeNET is a discovery platform designed to address a variety of questions concerning the genetic underpinning of human diseases. DisGeNET is one of the largest and comprehensive repositories of human gene-disease associations (GDAs) currently available. It also offers a set of bioinformatic tools to facilitate the analysis of these data by different user profiles. It is maintained by the Integrative Biomedical Informatics (IBI) Group, of the (GRIB)-IMIM/UPF, based at the Barcelona Biomedical Research Park (PRBB), Barcelona, Spain.
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.
In molecular biology, PathoPhenoDB is a biological database created by Kafkas et al. This database connects pathogens to their phenotypes using multiple databases such as NCBI, Human Disease OntologyHuman Phenotype Ontology, Mammalian Phenotype Ontology, PubChem, SIDER and CARD. Pathogen-disease associations were gathered mainly on CDC and the List of Infectious Diseases page on Wikipedia. The manner by which they assigned taxonomy was semi-automatic. When mapped against NCBI Taxonomy, if the pathogen was not an exact match, it is then mapped to the parent class. PathoPhenoDB employs NPMI in order to filter pairs based on their co-occurrence statistics.
