In genetics, the phenotype is the set of observable characteristics or traits of an organism. The term covers the organism's morphology, its developmental processes, its biochemical and physiological properties, its behavior, and the products of behavior. An organism's phenotype results from two basic factors: the expression of an organism's genetic code and the influence of environmental factors. Both factors may interact, further affecting the phenotype. When two or more clearly different phenotypes exist in the same population of a species, the species is called polymorphic. A well-documented example of polymorphism is Labrador Retriever coloring; while the coat color depends on many genes, it is clearly seen in the environment as yellow, black, and brown. Richard Dawkins in 1978 and then again in his 1982 book The Extended Phenotype suggested that one can regard bird nests and other built structures such as caddisfly larva cases and beaver dams as "extended phenotypes".
In information science, an ontology encompasses a representation, formal naming, and definitions of the categories, properties, and relations between the concepts, data, or entities that pertain to one, many, or all domains of discourse. More simply, an ontology is a way of showing the properties of a subject area and how they are related, by defining a set of terms and relational expressions that represent the entities in that subject area. The field which studies ontologies so conceived is sometimes referred to as applied ontology.
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. 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, human, and five other species.
The Open Biological and Biomedical Ontologies (OBO) Foundry is a group of people who 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 Saccharomyces Genome Database (SGD) is a scientific database of the molecular biology and genetics of the yeast Saccharomyces cerevisiae, which is commonly known as baker's or budding yeast. Further information is located at the Yeastract curated repository.
Integrative bioinformatics is a discipline of bioinformatics that focuses on problems of data integration for the life sciences.
The Foundational Model of Anatomy Ontology (FMA) is a reference ontology for the domain of human anatomy. It is a symbolic representation of the canonical, phenotypic structure of an organism; a spatial-structural ontology of anatomical entities and relations which form the physical organization of an organism at all salient levels of granularity.
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).
Xenbase is a Model Organism Database (MOD), providing informatics resources, as well as genomic and biological data on Xenopus frogs. Xenbase has been available since 1999, and covers both X. laevis and X. tropicalis Xenopus varieties. As of 2013 all of its services are running on virtual machines in a private cloud environment, making it one of the first MODs to do so. Other than hosting genomics data and tools, Xenbase supports the Xenopus research community though profiles for researchers and laboratories, and job and events postings.
SUPERFAMILY is a database and search platform of structural and functional annotation for all proteins and genomes. It classifies amino acid sequences into known structural domains, especially into SCOP superfamilies. Domains are functional, structural, and evolutionary units that form proteins. Domains of common Ancestry are grouped into superfamilies. The domains and domain superfamilies are defined and described in SCOP. Superfamilies are groups of proteins which have structural evidence to support a common evolutionary ancestor but may not have detectable sequence homology.
Virtual Fly Brain, or VFB, is an interactive, web-based tool that allows neurobiologists to explore the detailed neuroanatomy, transgene expression and associated phenotypes of the Drosophila melanogaster brain. Users can browse painted 3D image stacks of the Drosophila brain, choosing any plane of section they want and clicking on painted regions to find names' definitions, references and synonyms for the chosen region. For each region, they can run queries to find neurons, transgene expression and phenotypes. For each neuron found, users can browse definitions, references and synonyms.
The Uber-anatomy ontology (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 Human Phenotype Ontology (HPO) is a formal ontology of human phenotypes. Developed as part of the Monarch Initiative 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.
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.
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.
Canto is a web-based tool to support the curation of gene-specific scientific data, by both professional biocurators and publication authors. Canto was developed as part of the PomBase project, and is funded by the Wellcome Trust.
Melissa Anne Haendel is an American bioinformaticist who is the Sarah Graham Kenan Distinguished Professor at the UNC School of Medicine. She is also the Director of Precision Health & Translational Informatics, deputy director of Computational Science at The North Carolina Translational and Clinical Sciences Institute. She serves as Director of the Center for Data to Health (CD2H). Her research makes use of data to improve the discovery and diagnosis of diseases. During the COVID-19 pandemic, Haendel joined with the National Institutes of Health to launch the National COVID Cohort Collaborative (N3C), which looks to identify the risk factors that can predict severity of disease outcome and help to identify treatments.
