Journal ArticleDOI
Disease gene discovery through integrative genomics
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TLDR
Some of the emerging genomics technologies and data resources that can be used to infer gene function to prioritize candidate genes and how such approaches have recently been applied to discover genes underlying Mendelian disorders are reviewed.Abstract:
Ke yW ords human genetics, positional cloning, functional genomics, machine learning ■ Abstract The availability of complete genome sequences and the wealth of large- scale biological data sets now provide an unprecedented opportunity to elucidate the genetic basis of rare and common human diseases. Here we review some of the emerg- ing genomics technologies and data resources that can be used to infer gene function to prioritize candidate genes. We then describe some computational strategies for integrat- ing these large-scale data sets to provide more faithful descriptions of gene function, and how such approaches have recently been applied to discover genes underlying Mendelian disorders. Finally, we discuss future prospects and challenges for using integrative genomics to systematically discover not only single genes but also entire gene networks that underlie and modify human disease.read more
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Guidelines for investigating causality of sequence variants in human disease
Daniel G. MacArthur,Teri A. Manolio,David Dimmock,Heidi L. Rehm,Jay Shendure,Gonçalo R. Abecasis,David R. Adams,Russ B. Altman,Stylianos E. Antonarakis,Euan A. Ashley,Jeffrey C. Barrett,Leslie G. Biesecker,Donald F. Conrad,Gregory M. Cooper,Nancy J. Cox,Mark J. Daly,Mark Gerstein,David Goldstein,Joel N. Hirschhorn,Suzanne M. Leal,Len A. Pennacchio,John A. Stamatoyannopoulos,Shamil R. Sunyaev,David Valle,Benjamin F. Voight,Wendy Winckler,Chris Gunter +26 more
TL;DR: The key challenges of assessing sequence variants in human disease are discussed, integrating both gene-level and variant-level support for causality and guidelines for summarizing confidence in variant pathogenicity are proposed.
Journal ArticleDOI
The implications of human metabolic network topology for disease comorbidity
Deok-Sun Lee,Juyong Park,Juyong Park,Krin A. Kay,Nicholas A. Christakis,Zoltán N. Oltvai,Albert-László Barabási,Albert-László Barabási +7 more
TL;DR: In this article, a bipartite human disease association network is constructed, where nodes are diseases and two diseases are linked if mutated enzymes associated with them catalyze adjacent metabolic reactions.
Journal ArticleDOI
Genome-wide inferring gene–phenotype relationship by walking on the heterogeneous network
Yongjin Li,Jagdish C. Patra +1 more
TL;DR: A heterogeneous network is constructed by connecting the gene network and phenotype network using the phenotype-gene relationship information from the OMIM database using leave-one-out cross-validation to evaluate the ability of finding the gene-phenotype relationship.
Journal ArticleDOI
Systems medicine: the future of medical genomics and healthcare
TL;DR: It is recommended that systems medicine should be developed through an international network of systems biology and medicine centers dedicated to inter-disciplinary training and education, to help reduce the gap in healthcare between developed and developing countries.
Journal ArticleDOI
Improved human disease candidate gene prioritization using mouse phenotype
Jing Chen,Jing Chen,Huan Xu,Bruce J. Aronow,Bruce J. Aronow,Bruce J. Aronow,Anil G. Jegga,Anil G. Jegga +7 more
TL;DR: The incorporation of phenotype information for mouse orthologs of human genes greatly improves the human disease candidate gene analysis and prioritization.
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TL;DR: The results of an international collaboration to produce and make freely available a draft sequence of the human genome are reported and an initial analysis is presented, describing some of the insights that can be gleaned from the sequence.
Journal ArticleDOI
Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Journal ArticleDOI
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Journal ArticleDOI
Significance analysis of microarrays applied to the ionizing radiation response
TL;DR: A method that assigns a score to each gene on the basis of change in gene expression relative to the standard deviation of repeated measurements is described, suggesting that this repair pathway for UV-damaged DNA might play a previously unrecognized role in repairing DNA damaged by ionizing radiation.