article Open AccessTop 10% cited
An integrative approach to ortholog prediction for disease-focused and other functional studies
BMC Bioinformatics · 2011 · Vol. 12(1) · pp. 357–357
Yanhui Hu✉(Harvard University)I. R. Flockhart(Harvard University)Arunachalam Vinayagam(Harvard University)Clemens Bergwitz(Massachusetts General Hospital)Bonnie Berger(Massachusetts Institute of Technology)Norbert Perrimon(Howard Hughes Medical Institute)Stephanie E. Mohr(Harvard University)
Abstract
DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.
Bioinformatics and Genomic NetworksGenetics, Aging, and Longevity in Model OrganismsMachine Learning in BioinformaticsIdentification (biology)BiologyComputational biologyGeneGenomeMendelian inheritanceGeneticsFunction (biology)GenomicsPhenome
MeSH terms
AnimalsDiseaseDisease Models, AnimalHumansEvolution, MolecularGenetic Predisposition to DiseaseDatabases, GeneticGenome-Wide Association Study
Funding
- Howard Hughes Medical Institute
- Harvard Catalyst
- National Institutes of Health
- National Institute of Diabetes and Digestive and Kidney Diseases
Citations
886
FWCI
3.46
field-weighted impact
References
75
Percentile
93%
vs. same field & year
Citations per year
References
OrthoMCL: Identification of Ortholog Groups for Eukaryotic Genomes
Genome Research · 2003 · 6,112 citations
Database resources of the National Center for Biotechnology Information: update
Nucleic Acids Research · 2003 · 11,003 citations
EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates
Genome Research · 2008 · 1,324 citations
The COG database: an updated version includes eukaryotes
BMC Bioinformatics · 2003 · 4,484 citations
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