Research Topics
| Chad L MyersSummaryAffiliation: Princeton University Country: USA Publications
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Detail Information
Publications
Finding function: evaluation methods for functional genomic dataChad L Myers
Department of Computer Science, Princeton University, Princeton, NJ 08544, USA
BMC Genomics 7:187. 2006..These problems make it essentially impossible to compare computational methods or large-scale experimental datasets and also result in conclusions that generalize poorly in most biological applications...- Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiaeTeresa Reguly
Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto ON M5G 1X5, Canada
J Biol 5:11. 2006..Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference... - Visualization-based discovery and analysis of genomic aberrations in microarray dataChad L Myers
Lewis Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, NJ 08544, USA
BMC Bioinformatics 6:146. 2005..However, accurate identification of amplified or deleted regions requires a combination of visual and computational analysis of these microarray data... - Discovery of biological networks from diverse functional genomic dataChad L Myers
Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ 08544, USA
Genome Biol 6:R114. 2005..Our system, bioPIXIE, a public, comprehensive system for integration, analysis, and visualization of biological network predictions for S. cerevisiae, is freely accessible over the worldwide web... - A genomewide functional network for the laboratory mouseYuanfang Guan
Lewis Sigler Institute for Integrative Genomics, Carl Icahn Laboratory, Princeton University, Princeton, New Jersey, United States of America
PLoS Comput Biol 4:e1000165. 2008..princeton.edu... - Exploring the functional landscape of gene expression: directed search of large microarray compendiaMatthew A Hibbs
Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
Bioinformatics 23:2692-9. 2007..This vast repository is still underutilized due to the lack of methods for fast, accurate exploration of the entire compendium... - Nearest Neighbor Networks: clustering expression data based on gene neighborhoodsCurtis Huttenhower
Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
BMC Bioinformatics 8:250. 2007..g. ribosomes)... - Computational analysis of the yeast proteome: understanding and exploiting functional specificity in genomic dataCurtis Huttenhower
Department of Computer Science, Princeton University, Princeton, NJ 08544, USA
Methods Mol Biol 548:273-93. 2009..An awareness of these considerations can greatly improve the evaluation and analysis of any high-throughput experimental dataset... - Directing experimental biology: a case study in mitochondrial biogenesisMatthew A Hibbs
Lewis Sigler Institute for Integrative Genomics, Princeton University, Carl Icahn Laboratory, Princeton, New Jersey, United States of America
PLoS Comput Biol 5:e1000322. 2009..While this study focused on a specific functional area in yeast, many of these observations may be useful in the contexts of other processes and organisms... - The impact of incomplete knowledge on evaluation: an experimental benchmark for protein function predictionCurtis Huttenhower
Department of Computer Science, Princeton University, Princeton, NJ 08540 5233, USA
Bioinformatics 25:2404-10. 2009..Since gene annotation is incomplete for even the best studied model organisms, the biological reliability of such evaluations may be called into question... - Computationally driven, quantitative experiments discover genes required for mitochondrial biogenesisDavid C Hess
Lewis Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA
PLoS Genet 5:e1000407. 2009..Our results demonstrate that by leveraging computational analysis to direct quantitative experimental assays, we have characterized mutants with subtle mitochondrial defects whose phenotypes were undetected by high-throughput methods... - Predicting gene function in a hierarchical context with an ensemble of classifiersYuanfang Guan
Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
Genome Biol 9:S3. 2008..A recent mouse function prediction project (MouseFunc) brought together nine bioinformatics teams applying a diverse array of methodologies to mount the first large-scale effort to predict gene function in the laboratory mouse... - GOLEM: an interactive graph-based gene-ontology navigation and analysis toolRachel S G Sealfon
Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA
BMC Bioinformatics 7:443. 2006..Furthermore, most existing tools are web-based or require an Internet connection, will not load local annotations files, and provide either analysis or visualization functionality, but not both... - Context-sensitive data integration and prediction of biological networksChad L Myers
Department of Computer Science, Princeton University, 35 Olden Street, Princeton, NJ, USA
Bioinformatics 23:2322-30. 2007..Accounting for this variation can significantly improve network prediction, but to our knowledge, no previous approaches have explicitly leveraged this critical information about biological context... - Adenovirus type 5 exerts genome-wide control over cellular programs governing proliferation, quiescence, and survivalDaniel L Miller
Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
Genome Biol 8:R58. 2007..However, a global view of the effects of Ad5 infection on such programs in normal human cells is not available, despite widespread efforts to develop adenoviruses for therapeutic applications... - Global analysis of gene function in yeast by quantitative phenotypic profilingJames A Brown
Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305 5152, USA
Mol Syst Biol 2:2006.0001. 2006..This method will be useful when used alone and in conjunction with other global approaches to identify gene function in yeast... - Accurate detection of aneuploidies in array CGH and gene expression microarray dataChad L Myers
Lewis-Sigler Institute for Integrative Genomics, Carl Icahn Laboratory
Bioinformatics 20:3533-43. 2004..AVAILABILITY: Code available by request from the authors and on Web supplement at http://function.cs.princeton.edu/ChARM/.. - A critical assessment of Mus musculus gene function prediction using integrated genomic evidenceLourdes Pena-Castillo
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON M5S3E1, Canada
Genome Biol 9:S2. 2008..Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated...