Integrating Interactomes

[1]  M. Gerstein,et al.  Relating whole-genome expression data with protein-protein interactions. , 2002, Genome research.

[2]  M. Gerstein,et al.  Beyond synexpression relationships: local clustering of time-shifted and inverted gene expression profiles identifies new, biologically relevant interactions. , 2001, Journal of molecular biology.

[3]  Gary D Bader,et al.  A Combined Experimental and Computational Strategy to Define Protein Interaction Networks for Peptide Recognition Modules , 2001, Science.

[4]  G. Church,et al.  Correlation between transcriptome and interactome mapping data from Saccharomyces cerevisiae , 2001, Nature Genetics.

[5]  M. Gerstein,et al.  Interrelating different types of genomic data, from proteome to secretome: 'oming in on function. , 2001, Genome research.

[6]  R. Ozawa,et al.  A comprehensive two-hybrid analysis to explore the yeast protein interactome , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[7]  B. Schwikowski,et al.  A network of protein–protein interactions in yeast , 2000, Nature Biotechnology.

[8]  G. Church,et al.  A computational analysis of whole-genome expression data reveals chromosomal domains of gene expression , 2000, Nature Genetics.

[9]  M. Gerstein,et al.  The current excitement in bioinformatics-analysis of whole-genome expression data: how does it relate to protein structure and function? , 2000, Current opinion in structural biology.

[10]  M Gerstein,et al.  Genome-wide analysis relating expression level with protein subcellular localization. , 2000, Trends in genetics : TIG.

[11]  M. Gerstein,et al.  A Bayesian system integrating expression data with sequence patterns for localizing proteins: comprehensive application to the yeast genome. , 2000, Journal of molecular biology.

[12]  Yudong D. He,et al.  Functional Discovery via a Compendium of Expression Profiles , 2000, Cell.

[13]  D. Eisenberg,et al.  Protein function in the post-genomic era , 2000, Nature.

[14]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[15]  M Gerstein,et al.  Analysis of the yeast transcriptome with structural and functional categories: characterizing highly expressed proteins. , 2000, Nucleic acids research.

[16]  James R. Knight,et al.  A comprehensive analysis of protein–protein interactions in Saccharomyces cerevisiae , 2000, Nature.

[17]  D Haussler,et al.  Knowledge-based analysis of microarray gene expression data by using support vector machines. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[18]  Kei-Hoi Cheung,et al.  Large-scale analysis of the yeast genome by transposon tagging and gene disruption , 1999, Nature.

[19]  D. Eisenberg,et al.  A combined algorithm for genome-wide prediction of protein function , 1999, Nature.

[20]  Ronald W. Davis,et al.  Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. , 1999, Science.

[21]  D. Eisenberg,et al.  Detecting protein function and protein-protein interactions from genome sequences. , 1999, Science.

[22]  G. Church,et al.  Systematic determination of genetic network architecture , 1999, Nature Genetics.

[23]  J. Mesirov,et al.  Interpreting patterns of gene expression with self-organizing maps: methods and application to hematopoietic differentiation. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[24]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[25]  G. Church,et al.  Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation , 1998, Nature Biotechnology.

[26]  Ronald W. Davis,et al.  A genome-wide transcriptional analysis of the mitotic cell cycle. , 1998, Molecular cell.