The Mammalian Phenotype Ontology as a tool for annotating, analyzing and comparing phenotypic information

The Mammalian Phenotype (MP) Ontology enables robust annotation of mammalian phenotypes in the context of mutations, quantitative trait loci and strains that are used as models of human biology and disease. The MP Ontology supports different levels and richness of phenotypic knowledge and flexible annotations to individual genotypes. It continues to develop dynamically via collaborative input from research groups, mutagenesis consortia, and biological domain experts. The MP Ontology is currently used by the Mouse Genome Database and Rat Genome Database to represent phenotypic data

Cancer Biology Data Curation at the Mouse Tumor Biology Database (MTB)

Many advances in the field of cancer biology have been made using mouse models of human cancer. The Mouse Tumor Biology (MTB, "http://tumor.informatics.jax.org":http://tumor.informatics.jax.org) database provides web-based access to data on spontaneous and induced tumors from genetically defined mice (inbred, hybrid, mutant, and genetically engineered strains of mice). These data include standardized tumor names and classifications, pathology reports and images, mouse genetics, genomic and cytogenetic changes occurring in the tumor, strain names, tumor frequency and latency, and literature citations.

Although primary source for the data represented in MTB is peer-reviewed scientific literature an increasing amount of data is derived from disparate sources. MTB includes annotated histopathology images and cytogenetic assay images for mouse tumors where these data are available from The Jackson Laboratory’s mouse colonies and from outside contributors. MTB encourages direct submission of mouse tumor data and images from the cancer research community and provides investigators with a web-accessible tool for image submission and annotation. 

Integrated searches of the data in MTB are facilitated by the use of several controlled vocabularies and by adherence to standard nomenclature. MTB also provides links to other related online resources such as the Mouse Genome Database, Mouse Phenome Database, the Biology of the Mammary Gland Web Site, Festing's Listing of Inbred Strains of Mice, the JAX® Mice Web Site, and the Mouse Models of Human Cancers Consortium's Mouse Repository. 

MTB provides access to data on mouse models of cancer via the internet and has been designed to facilitate the selection of experimental models for cancer research, the evaluation of mouse genetic models of human cancer, the review of patterns of mutations in specific cancers, and the identification of genes that are commonly mutated across a spectrum of cancers.

MTB is supported by NCI grant CA089713

The mouse genome database (MGD): new features facilitating a model system

The mouse genome database (MGD, ), the international community database for mouse, provides access to extensive integrated data on the genetics, genomics and biology of the laboratory mouse. The mouse is an excellent and unique animal surrogate for studying normal development and disease processes in humans. Thus, MGD's primary goals are to facilitate the use of mouse models for studying human disease and enable the development of translational research hypotheses based on comparative genotype, phenotype and functional analyses. Core MGD data content includes gene characterization and functions, phenotype and disease model descriptions, DNA and protein sequence data, polymorphisms, gene mapping data and genome coordinates, and comparative gene data focused on mammals. Data are integrated from diverse sources, ranging from major resource centers to individual investigator laboratories and the scientific literature, using a combination of automated processes and expert human curation. MGD collaborates with the bioinformatics community on the development of data and semantic standards, and it incorporates key ontologies into the MGD annotation system, including the Gene Ontology (GO), the Mammalian Phenotype Ontology, and the Anatomical Dictionary for Mouse Development and the Adult Anatomy. MGD is the authoritative source for mouse nomenclature for genes, alleles, and mouse strains, and for GO annotations to mouse genes. MGD provides a unique platform for data mining and hypothesis generation where one can express complex queries simultaneously addressing phenotypic effects, biochemical function and process, sub-cellular location, expression, sequence, polymorphism and mapping data. Both web-based querying and computational access to data are provided. Recent improvements in MGD described here include the incorporation of single nucleotide polymorphism data and search tools, the addition of PIR gene superfamily classifications, phenotype data for NIH-acquired knockout mice, images for mouse phenotypic genotypes, new functional graph displays of GO annotations, and new orthology displays including sequence information and graphic displays

The Mouse Genome Database (MGD): from genes to mice—a community resource for mouse biology

The Mouse Genome Database (MGD) forms the core of the Mouse Genome Informatics (MGI) system (http://www.informatics.jax.org), a model organism database resource for the laboratory mouse. MGD provides essential integration of experimental knowledge for the mouse system with information annotated from both literature and online sources. MGD curates and presents consensus and experimental data representations of genotype (sequence) through phenotype information, including highly detailed reports about genes and gene products. Primary foci of integration are through representations of relationships among genes, sequences and phenotypes. MGD collaborates with other bioinformatics groups to curate a definitive set of information about the laboratory mouse and to build and implement the data and semantic standards that are essential for comparative genome analysis. Recent improvements in MGD discussed here include the enhancement of phenotype resources, the re-development of the International Mouse Strain Resource, IMSR, the update of mammalian orthology datasets and the electronic publication of classic books in mouse genetics

Disease Ontology: improving and unifying disease annotations across species.

Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD\u27s and RGD\u27s disease term annotations identified new terms that enhance DO\u27s representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO\u27s domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO\u27s usability across human data, MGD, RGD and the rest of the model organism database community. Dis Model Mech 2018 Mar 12;11(3):dmm032839

The Mouse Genome Database: enhancements and updates

The Mouse Genome Database (MGD) is a major component of the Mouse Genome Informatics (MGI, http://www.informatics.jax.org/) database resource and serves as the primary community model organism database for the laboratory mouse. MGD is the authoritative source for mouse gene, allele and strain nomenclature and for phenotype and functional annotations of mouse genes. MGD contains comprehensive data and information related to mouse genes and their functions, standardized descriptions of mouse phenotypes, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information including comparative data on mammalian genes. Data for MGD are obtained from diverse sources including manual curation of the biomedical literature and direct contributions from individual investigator’s laboratories and major informatics resource centers, such as Ensembl, UniProt and NCBI. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology and the Mammalian Phenotype Ontology. Recent improvements in MGD described here includes integration of mouse gene trap allele and sequence data, integration of gene targeting information from the International Knockout Mouse Consortium, deployment of an MGI Biomart, and enhancements to our batch query capability for customized data access and retrieval

Finding and sharing: new approaches to registries of databases and services for the biomedical sciences

The recent explosion of biological data and the concomitant proliferation of distributed databases make it challenging for biologists and bioinformaticians to discover the best data resources for their needs, and the most efficient way to access and use them. Despite a rapid acceleration in uptake of syntactic and semantic standards for interoperability, it is still difficult for users to find which databases support the standards and interfaces that they need. To solve these problems, several groups are developing registries of databases that capture key metadata describing the biological scope, utility, accessibility, ease-of-use and existence of web services allowing interoperability between resources. Here, we describe some of these initiatives including a novel formalism, the Database Description Framework, for describing database operations and functionality and encouraging good database practise. We expect such approaches will result in improved discovery, uptake and utilization of data resources. Database URL: http://www.casimir.org.uk/casimir_dd

Towards BioDBcore: a community-defined information specification for biological databases

The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological database

The Human Phenotype Ontology project:linking molecular biology and disease through phenotype data

The Human Phenotype Ontology (HPO) project, available at http://www.human-phenotype-ontology.org, provides a structured, comprehensive and well-defined set of 10,088 classes (terms) describing human phenotypic abnormalities and 13,326 subclass relations between the HPO classes. In addition we have developed logical definitions for 46% of all HPO classes using terms from ontologies for anatomy, cell types, function, embryology, pathology and other domains. This allows interoperability with several resources, especially those containing phenotype information on model organisms such as mouse and zebrafish. Here we describe the updated HPO database, which provides annotations of 7,278 human hereditary syndromes listed in OMIM, Orphanet and DECIPHER to classes of the HPO. Various meta-attributes such as frequency, references and negations are associated with each annotation. Several large-scale projects worldwide utilize the HPO for describing phenotype information in their datasets. We have therefore generated equivalence mappings to other phenotype vocabularies such as LDDB, Orphanet, MedDRA, UMLS and phenoDB, allowing integration of existing datasets and interoperability with multiple biomedical resources. We have created various ways to access the HPO database content using flat files, a MySQL database, and Web-based tools. All data and documentation on the HPO project can be found online