Christopher J. Mungall
Lawrence Berkeley National Laboratory
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Publication
Featured researches published by Christopher J. Mungall.
Nucleic Acids Research | 2004
Midori A. Harris; Jennifer I. Clark; Amelia Ireland; Jane Lomax; Michael Ashburner; R. Foulger; K. Eilbeck; Suzanna E. Lewis; B. Marshall; Christopher J. Mungall; John Richter; Gerald M. Rubin; Judith A. Blake; Mary E. Dolan; Harold J. Drabkin; Janan T. Eppig; David P. Hill; Li Ni; Martin Ringwald; Rama Balakrishnan; J. M. Cherry; Karen R. Christie; Maria C. Costanzo; Selina S. Dwight; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Eurie L. Hong; Robert S. Nash; Anand Sethuraman
The Gene Ontology (GO) project (http://www. geneontology.org/) provides structured, controlled vocabularies and classifications that cover several domains of molecular and cellular biology and are freely available for community use in the annotation of genes, gene products and sequences. Many model organism databases and genome annotation groups use the GO and contribute their annotation sets to the GO resource. The GO database integrates the vocabularies and contributed annotations and provides full access to this information in several formats. Members of the GO Consortium continually work collectively, involving outside experts as needed, to expand and update the GO vocabularies. The GO Web resource also provides access to extensive documentation about the GO project and links to applications that use GO data for functional analyses.
Nature | 2014
Robin Andersson; Claudia Gebhard; Irene Miguel-Escalada; Ilka Hoof; Jette Bornholdt; Mette Boyd; Yun Chen; Xiaobei Zhao; Christian Schmidl; Takahiro Suzuki; Evgenia Ntini; Erik Arner; Eivind Valen; Kang Li; Lucia Schwarzfischer; Dagmar Glatz; Johanna Raithel; Berit Lilje; Nicolas Rapin; Frederik Otzen Bagger; Mette Jørgensen; Peter Refsing Andersen; Nicolas Bertin; Owen J. L. Rackham; A. Maxwell Burroughs; J. Kenneth Baillie; Yuri Ishizu; Yuri Shimizu; Erina Furuhata; Shiori Maeda
Enhancers control the correct temporal and cell-type-specific activation of gene expression in multicellular eukaryotes. Knowing their properties, regulatory activity and targets is crucial to understand the regulation of differentiation and homeostasis. Here we use the FANTOM5 panel of samples, covering the majority of human tissues and cell types, to produce an atlas of active, in vivo-transcribed enhancers. We show that enhancers share properties with CpG-poor messenger RNA promoters but produce bidirectional, exosome-sensitive, relatively short unspliced RNAs, the generation of which is strongly related to enhancer activity. The atlas is used to compare regulatory programs between different cells at unprecedented depth, to identify disease-associated regulatory single nucleotide polymorphisms, and to classify cell-type-specific and ubiquitous enhancers. We further explore the utility of enhancer redundancy, which explains gene expression strength rather than expression patterns. The online FANTOM5 enhancer atlas represents a unique resource for studies on cell-type-specific enhancers and gene regulation.
Bioinformatics | 2009
Seth Carbon; Amelia Ireland; Christopher J. Mungall; ShengQiang Shu; Brad Marshall; Suzanna E. Lewis
AmiGO is a web application that allows users to query, browse and visualize ontologies and related gene product annotation (association) data. AmiGO can be used online at the Gene Ontology (GO) website to access the data provided by the GO Consortium1; it can also be downloaded and installed to browse local ontologies and annotations.2 AmiGO is free open source software developed and maintained by the GO Consortium. Availability: http://amigo.geneontology.org Download: http://sourceforge.net/projects/geneontology/ Contact: [email protected]
Genome Biology | 2005
Barry Smith; Werner Ceusters; Bert Klagges; Jacob Köhler; Anand Kumar; Jane Lomax; Christopher J. Mungall; Fabian Neuhaus; Alan L. Rector; Cornelius Rosse
To enhance the treatment of relations in biomedical ontologies we advance a methodology for providing consistent and unambiguous formal definitions of the relational expressions used in such ontologies in a way designed to assist developers and users in avoiding errors in coding and annotation. The resulting Relation Ontology can promote interoperability of ontologies and support new types of automated reasoning about the spatial and temporal dimensions of biological and medical phenomena.
Proceedings of the National Academy of Sciences of the United States of America | 2008
Barret D. Pfeiffer; Arnim Jenett; Ann S. Hammonds; Teri-T B. Ngo; Sima Misra; Christine Murphy; Audra Scully; Joseph W. Carlson; Kenneth H. Wan; Todd R. Laverty; Christopher J. Mungall; Rob Svirskas; James T. Kadonaga; Chris Q. Doe; Michael B. Eisen; Susan E. Celniker; Gerald M. Rubin
We demonstrate the feasibility of generating thousands of transgenic Drosophila melanogaster lines in which the expression of an exogenous gene is reproducibly directed to distinct small subsets of cells in the adult brain. We expect the expression patterns produced by the collection of 5,000 lines that we are currently generating to encompass all neurons in the brain in a variety of intersecting patterns. Overlapping 3-kb DNA fragments from the flanking noncoding and intronic regions of genes thought to have patterned expression in the adult brain were inserted into a defined genomic location by site-specific recombination. These fragments were then assayed for their ability to function as transcriptional enhancers in conjunction with a synthetic core promoter designed to work with a wide variety of enhancer types. An analysis of 44 fragments from four genes found that >80% drive expression patterns in the brain; the observed patterns were, on average, comprised of <100 cells. Our results suggest that the D. melanogaster genome contains >50,000 enhancers and that multiple enhancers drive distinct subsets of expression of a gene in each tissue and developmental stage. We expect that these lines will be valuable tools for neuroanatomy as well as for the elucidation of neuronal circuits and information flow in the fly brain.
Genome Biology | 2005
Karen Eilbeck; Suzanna E. Lewis; Christopher J. Mungall; Mark Yandell; Lincoln Stein; Richard Durbin; Michael Ashburner
The Sequence Ontology (SO) is a structured controlled vocabulary for the parts of a genomic annotation. SO provides a common set of terms and definitions that will facilitate the exchange, analysis and management of genomic data. Because SO treats part-whole relationships rigorously, data described with it can become substrates for automated reasoning, and instances of sequence features described by the SO can be subjected to a group of logical operations termed extensional mereology operators.
Nucleic Acids Research | 2008
Midori A. Harris; Jennifer I. Deegan; Amelia Ireland; Jane Lomax; Michael Ashburner; Susan Tweedie; Seth Carbon; Suzanna E. Lewis; Christopher J. Mungall; John Richter; Karen Eilbeck; Judith A. Blake; Alexander D. Diehl; Mary E. Dolan; Harold Drabkin; Janan T. Eppig; David P. Hill; Ni Li; Martin Ringwald; Rama Balakrishnan; Gail Binkley; J. Michael Cherry; Karen R. Christie; Maria C. Costanzo; Qing Dong; Stacia R. Engel; Dianna G. Fisk; Jodi E. Hirschman; Benjamin C. Hitz; Eurie L. Hong
The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.
Nucleic Acids Research | 2014
Sebastian Köhler; Sandra C. Doelken; Christopher J. Mungall; Sebastian Bauer; Helen V. Firth; Isabelle Bailleul-Forestier; Graeme C.M. Black; Danielle L. Brown; Michael Brudno; Jennifer Campbell; David Fitzpatrick; Janan T. Eppig; Andrew P. Jackson; Kathleen Freson; Marta Girdea; Ingo Helbig; Jane A. Hurst; Johanna A. Jähn; Laird G. Jackson; Anne M. Kelly; David H. Ledbetter; Sahar Mansour; Christa Lese Martin; Celia Moss; Andrew D Mumford; Willem H. Ouwehand; Soo Mi Park; Erin Rooney Riggs; Richard H. Scott; Sanjay M. Sisodiya
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.
Genome Research | 2009
Mitchell E. Skinner; Andrew V. Uzilov; Lincoln Stein; Christopher J. Mungall; Ian Holmes
We describe an open source, portable, JavaScript-based genome browser, JBrowse, that can be used to navigate genome annotations over the web. JBrowse helps preserve the users sense of location by avoiding discontinuous transitions, instead offering smoothly animated panning, zooming, navigation, and track selection. Unlike most existing genome browsers, where the genome is rendered into images on the webserver and the role of the client is restricted to displaying those images, JBrowse distributes work between the server and client and therefore uses significantly less server overhead than previous genome browsers. We report benchmark results empirically comparing server- and client-side rendering strategies, review the architecture and design considerations of JBrowse, and describe a simple wiki plug-in that allows users to upload and share annotation tracks.
Genome Biology | 2002
Suzanna E. Lewis; Smj Searle; Nomi L. Harris; M Gibson; Vivek Iyer; John Richter; C Wiel; Leyla Bayraktaroglu; Ewan Birney; Madeline A. Crosby; Joshua S Kaminker; Beverley B. Matthews; Se Prochnik; Christopher D. Smith; Jl Tupy; Gerald M. Rubin; S Misra; Christopher J. Mungall; Michele Clamp
The well-established inaccuracy of purely computational methods for annotating genome sequences necessitates an interactive tool to allow biological experts to refine these approximations by viewing and independently evaluating the data supporting each annotation. Apollo was developed to meet this need, enabling curators to inspect genome annotations closely and edit them. FlyBase biologists successfully used Apollo to annotate the Drosophila melanogaster genome and it is increasingly being used as a starting point for the development of customized annotation editing tools for other genome projects.