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Full-Text Articles in Medicine and Health Sciences
Analysis Of Genome-Wide Knockout Mouse Database Identifies Candidate Ciliopathy Genes., Kendall Higgins, Bret A Moore, Zorana Berberovic, Hibret A Adissu, Mohammad Eskandarian, Ann M Flenniken, Andy Shao, Denise M Imai, Dave Clary, Louise Lanoue, Susan Newbigging, Lauryl M J Nutter, David J Adams, Fatima Bosch, Robert Schneider, Steve D M Brown, Mary E Dickinson, Michael Dobbie, Paul Flicek, Xiang Gao, Sanjeev Galande, Anne Grobler, Jason D Heaney, Yann Herault, Martin Hrabe De Angelis, Hsian-Jean Genie Chin, Fabio Mammano, Chuan Qin, Toshihiko Shiroishi, Radislav Sedlacek, J-K Seong, Ying Xu, K C Kent Lloyd, Colin Mckerlie, Ala Moshiri
Analysis Of Genome-Wide Knockout Mouse Database Identifies Candidate Ciliopathy Genes., Kendall Higgins, Bret A Moore, Zorana Berberovic, Hibret A Adissu, Mohammad Eskandarian, Ann M Flenniken, Andy Shao, Denise M Imai, Dave Clary, Louise Lanoue, Susan Newbigging, Lauryl M J Nutter, David J Adams, Fatima Bosch, Robert Schneider, Steve D M Brown, Mary E Dickinson, Michael Dobbie, Paul Flicek, Xiang Gao, Sanjeev Galande, Anne Grobler, Jason D Heaney, Yann Herault, Martin Hrabe De Angelis, Hsian-Jean Genie Chin, Fabio Mammano, Chuan Qin, Toshihiko Shiroishi, Radislav Sedlacek, J-K Seong, Ying Xu, K C Kent Lloyd, Colin Mckerlie, Ala Moshiri
Faculty Research 2022
We searched a database of single-gene knockout (KO) mice produced by the International Mouse Phenotyping Consortium (IMPC) to identify candidate ciliopathy genes. We first screened for phenotypes in mouse lines with both ocular and renal or reproductive trait abnormalities. The STRING protein interaction tool was used to identify interactions between known cilia gene products and those encoded by the genes in individual knockout mouse strains in order to generate a list of "candidate ciliopathy genes." From this list, 32 genes encoded proteins predicted to interact with known ciliopathy proteins. Of these, 25 had no previously described roles in ciliary pathobiology. …
[Rare-Disease Data Standards]., Peter N Robinson, Holm Graessner
[Rare-Disease Data Standards]., Peter N Robinson, Holm Graessner
Faculty Research 2022
The use of standardized data formats (data standards) in healthcare supports four main goals: (1) exchange of data, (2) integration of computer systems and tools, (3) data storage and archiving, and (4) support of federated databases. Standards are especially important for rare-disease research and clinical care.In this review, we introduce healthcare standards and present a selection of standards that are commonly used in the field of rare diseases. The Human Phenotype Ontology (HPO) is the most commonly used standard for annotating phenotypic abnormalities and supporting phenotype-driven analysis of diagnostic exome and genome sequencing. Numerous standards for diseases are available that …
Musmorph, A Database Of Standardized Mouse Morphology Data For Morphometric Meta-Analyses., Jay Devine, Marta Vidal-García, Wei Liu, Amanda Neves, Lucas D Lo Vercio, Rebecca M Green, Heather A Richbourg, Marta Marchini, Colton M Unger, Audrey C Nickle, Bethany Radford, Nathan M Young, Paula N Gonzalez, Robert E Schuler, Alejandro Bugacov, Campbell Rolian, Christopher J Percival, Trevor Williams, Lee Niswander, Anne L Calof, Arthur D Lander, Axel Visel, Frank R Jirik, James M Cheverud, Ophir D Klein, Ramon Y Birnbaum, Amy E Merrill, Rebecca R Ackermann, Daniel Graf, Myriam Hemberger, Wendy Dean, Nils D Forkert, Stephen A. Murray, Henrik Westerberg, Ralph S Marcucio, Benedikt Hallgrímsson
Musmorph, A Database Of Standardized Mouse Morphology Data For Morphometric Meta-Analyses., Jay Devine, Marta Vidal-García, Wei Liu, Amanda Neves, Lucas D Lo Vercio, Rebecca M Green, Heather A Richbourg, Marta Marchini, Colton M Unger, Audrey C Nickle, Bethany Radford, Nathan M Young, Paula N Gonzalez, Robert E Schuler, Alejandro Bugacov, Campbell Rolian, Christopher J Percival, Trevor Williams, Lee Niswander, Anne L Calof, Arthur D Lander, Axel Visel, Frank R Jirik, James M Cheverud, Ophir D Klein, Ramon Y Birnbaum, Amy E Merrill, Rebecca R Ackermann, Daniel Graf, Myriam Hemberger, Wendy Dean, Nils D Forkert, Stephen A. Murray, Henrik Westerberg, Ralph S Marcucio, Benedikt Hallgrímsson
Faculty Research 2022
Complex morphological traits are the product of many genes with transient or lasting developmental effects that interact in anatomical context. Mouse models are a key resource for disentangling such effects, because they offer myriad tools for manipulating the genome in a controlled environment. Unfortunately, phenotypic data are often obtained using laboratory-specific protocols, resulting in self-contained datasets that are difficult to relate to one another for larger scale analyses. To enable meta-analyses of morphological variation, particularly in the craniofacial complex and brain, we created MusMorph, a database of standardized mouse morphology data spanning numerous genotypes and developmental stages, including E10.5, E11.5, …
A Simple Standard For Sharing Ontological Mappings (Sssom)., Nicolas Matentzoglu, James P Balhoff, Susan M. Bello, Chris Bizon, Matthew Brush, Tiffany J Callahan, Christopher G Chute, William D Duncan, Chris T Evelo, Davera Gabriel, John Graybeal, Alasdair Gray, Benjamin M Gyori, Melissa Haendel, Henriette Harmse, Nomi L Harris, Ian Harrow, Harshad B Hegde, Amelia L Hoyt, Charles T Hoyt, Dazhi Jiao, Ernesto Jiménez-Ruiz, Simon Jupp, Hyeongsik Kim, Sebastian Koehler, Thomas Liener, Qinqin Long, James Malone, James A Mclaughlin, Julie A Mcmurry, Sierra Moxon, Monica C Munoz-Torres, David Osumi-Sutherland, James A Overton, Bjoern Peters, Tim Putman, Núria Queralt-Rosinach, Kent Shefchek, Harold Solbrig, Anne Thessen, Tania Tudorache, Nicole Vasilevsky, Alex H Wagner, Christopher J Mungall
A Simple Standard For Sharing Ontological Mappings (Sssom)., Nicolas Matentzoglu, James P Balhoff, Susan M. Bello, Chris Bizon, Matthew Brush, Tiffany J Callahan, Christopher G Chute, William D Duncan, Chris T Evelo, Davera Gabriel, John Graybeal, Alasdair Gray, Benjamin M Gyori, Melissa Haendel, Henriette Harmse, Nomi L Harris, Ian Harrow, Harshad B Hegde, Amelia L Hoyt, Charles T Hoyt, Dazhi Jiao, Ernesto Jiménez-Ruiz, Simon Jupp, Hyeongsik Kim, Sebastian Koehler, Thomas Liener, Qinqin Long, James Malone, James A Mclaughlin, Julie A Mcmurry, Sierra Moxon, Monica C Munoz-Torres, David Osumi-Sutherland, James A Overton, Bjoern Peters, Tim Putman, Núria Queralt-Rosinach, Kent Shefchek, Harold Solbrig, Anne Thessen, Tania Tudorache, Nicole Vasilevsky, Alex H Wagner, Christopher J Mungall
Faculty Research 2022
Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that …
Harmonizing Model Organism Data In The Alliance Of Genome Resources., Alliance Of Genome Resources Consortium, Anna V. Anagnostopoulos, Susan M. Bello, Judith A. Blake, Olin Blodgett, Carol J. Bult, Karen R. Christie, Mary E. Dolan, Paul Hale, James A. Kadin, Monica S. Mcandrews, Howie Motenko, David R. Shaw, Constance M. Smith, Cynthia L. Smith, Monika Tomczuk, Laurens G. Wilming
Harmonizing Model Organism Data In The Alliance Of Genome Resources., Alliance Of Genome Resources Consortium, Anna V. Anagnostopoulos, Susan M. Bello, Judith A. Blake, Olin Blodgett, Carol J. Bult, Karen R. Christie, Mary E. Dolan, Paul Hale, James A. Kadin, Monica S. Mcandrews, Howie Motenko, David R. Shaw, Constance M. Smith, Cynthia L. Smith, Monika Tomczuk, Laurens G. Wilming
Faculty Research 2022
The Alliance of Genome Resources (the Alliance) is a combined effort of 7 knowledgebase projects: Saccharomyces Genome Database, WormBase, FlyBase, Mouse Genome Database, the Zebrafish Information Network, Rat Genome Database, and the Gene Ontology Resource. The Alliance seeks to provide several benefits: better service to the various communities served by these projects; a harmonized view of data for all biomedical researchers, bioinformaticians, clinicians, and students; and a more sustainable infrastructure. The Alliance has harmonized cross-organism data to provide useful comparative views of gene function, gene expression, and human disease relevance. The basis of the comparative views is shared calls of …
Mouse Genome Informatics (Mgi): Latest News From Mgd And Gxd., Martin Ringwald, Joel E Richardson, Richard M. Baldarelli, Judith A. Blake, James A. Kadin, Cynthia Smith, Carol J Bult
Mouse Genome Informatics (Mgi): Latest News From Mgd And Gxd., Martin Ringwald, Joel E Richardson, Richard M. Baldarelli, Judith A. Blake, James A. Kadin, Cynthia Smith, Carol J Bult
Faculty Research 2022
The Mouse Genome Informatics (MGI) database system combines multiple expertly curated community data resources into a shared knowledge management ecosystem united by common metadata annotation standards. MGI's mission is to facilitate the use of the mouse as an experimental model for understanding the genetic and genomic basis of human health and disease. MGI is the authoritative source for mouse gene, allele, and strain nomenclature and is the primary source of mouse phenotype annotations, functional annotations, developmental gene expression information, and annotations of mouse models with human diseases. MGI maintains mouse anatomy and phenotype ontologies and contributes to the development of …
The Human Disease Ontology 2022 Update., Lynn M Schriml, James B Munro, Mike Schor, Dustin Olley, Carrie Mccracken, Victor Felix, J Allen Baron, Rebecca Jackson, Susan M. Bello, Cynthia Bearer, Richard Lichenstein, Katharine Bisordi, Nicole Campion Dialo, Michelle Giglio, Carol Greene
The Human Disease Ontology 2022 Update., Lynn M Schriml, James B Munro, Mike Schor, Dustin Olley, Carrie Mccracken, Victor Felix, J Allen Baron, Rebecca Jackson, Susan M. Bello, Cynthia Bearer, Richard Lichenstein, Katharine Bisordi, Nicole Campion Dialo, Michelle Giglio, Carol Greene
Faculty Research 2022
The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO's 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10× increase in the past 5 years. The DO, funded as a NHGRI Genomic Resource, plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational research projects and …