Literature DB >> 11042457

The current excitement in bioinformatics-analysis of whole-genome expression data: how does it relate to protein structure and function?

M Gerstein1, R Jansen.   

Abstract

Whole-genome expression profiles provide a rich new data-trove for bioinformatics. Initial analyses of the profiles have included clustering and cross-referencing to 'external' information on protein structure and function. Expression profile clusters do relate to protein function, but the correlation is not perfect, with the discrepancies partially resulting from the difficulty in consistently defining function. Other attributes of proteins can also be related to expression-in particular, structure and localization-and sometimes show a clearer relationship than function.

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Year:  2000        PMID: 11042457     DOI: 10.1016/s0959-440x(00)00134-2

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  22 in total

1.  PartsList: a web-based system for dynamically ranking protein folds based on disparate attributes, including whole-genome expression and interaction information.

Authors:  J Qian; B Stenger; C A Wilson; J Lin; R Jansen; S A Teichmann; J Park; W G Krebs; H Yu; V Alexandrov; N Echols; M Gerstein
Journal:  Nucleic Acids Res       Date:  2001-04-15       Impact factor: 16.971

2.  Relating whole-genome expression data with protein-protein interactions.

Authors:  Ronald Jansen; Dov Greenbaum; Mark Gerstein
Journal:  Genome Res       Date:  2002-01       Impact factor: 9.043

3.  GeneCensus: genome comparisons in terms of metabolic pathway activity and protein family sharing.

Authors:  J Lin; J Qian; D Greenbaum; P Bertone; R Das; N Echols; A Senes; B Stenger; M Gerstein
Journal:  Nucleic Acids Res       Date:  2002-10-15       Impact factor: 16.971

4.  ExpressYourself: A modular platform for processing and visualizing microarray data.

Authors:  Nicholas M Luscombe; Thomas E Royce; Paul Bertone; Nathaniel Echols; Christine E Horak; Joseph T Chang; Michael Snyder; Mark Gerstein
Journal:  Nucleic Acids Res       Date:  2003-07-01       Impact factor: 16.971

5.  Integration of genomic datasets to predict protein complexes in yeast.

Authors:  Ronald Jansen; Ning Lan; Jiang Qian; Mark Gerstein
Journal:  J Struct Funct Genomics       Date:  2002

6.  Judging the quality of gene expression-based clustering methods using gene annotation.

Authors:  Francis D Gibbons; Frederick P Roth
Journal:  Genome Res       Date:  2002-10       Impact factor: 9.043

7.  A comparative cDNA microarray analysis reveals a spectrum of genes regulated by Pax6 in mouse lens.

Authors:  Bharesh K Chauhan; Nathan A Reed; Ying Yang; Lukás Cermák; Lixing Reneker; Melinda K Duncan; Ales Cvekl
Journal:  Genes Cells       Date:  2002-12       Impact factor: 1.891

Review 8.  Mass spectrometry-based proteomics and its application to studies of Porphyromonas gingivalis invasion and pathogenicity.

Authors:  Richard J Lamont; Marina Meila; Qiangwei Xia; Murray Hackett
Journal:  Infect Disord Drug Targets       Date:  2006-09

Review 9.  Structural and functional analysis of rice genome.

Authors:  Akhilesh K Tyagi; Jitendra P Khurana; Paramjit Khurana; Saurabh Raghuvanshi; Anumapa Gaur; Anita Kapur; Vikrant Gupta; Dibyendu Kumar; V Ravi; Shubha Vij; Parul Khurana; Sulabha Sharma
Journal:  J Genet       Date:  2004-04       Impact factor: 1.166

10.  The limitations of simple gene set enrichment analysis assuming gene independence.

Authors:  Pablo Tamayo; George Steinhardt; Arthur Liberzon; Jill P Mesirov
Journal:  Stat Methods Med Res       Date:  2012-10-14       Impact factor: 3.021

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