E M Marcotte

Summary

Affiliation: University of Texas
Country: USA

Publications

  1. ncbi request reprint Exploiting big biology: integrating large-scale biological data for function inference
    E Marcotte
    Department of Chemistry and Biochemistry and Institute for Cellular and Molecular Biology, University of Texas at Austin, 78712, USA
    Brief Bioinform 2:363-74. 2001
  2. pmc Systematic definition of protein constituents along the major polarization axis reveals an adaptive reuse of the polarization machinery in pheromone-treated budding yeast
    Rammohan Narayanaswamy
    Center for Systems and Synthetic Biology, Departments of Chemistry and Biochemistry, University of Texas, Austin, Texas 78712
    J Proteome Res 8:6-19. 2009
  3. pmc Integrating shotgun proteomics and mRNA expression data to improve protein identification
    Smriti R Ramakrishnan
    Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA
    Bioinformatics 25:1397-403. 2009
  4. pmc mspire: mass spectrometry proteomics in Ruby
    John T Prince
    Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA
    Bioinformatics 24:2796-7. 2008
  5. pmc Mechanisms of cell cycle control revealed by a systematic and quantitative overexpression screen in S. cerevisiae
    Wei Niu
    Center for Systems and Synthetic Biology, University of Texas, Austin, Texas, United States of America
    PLoS Genet 4:e1000120. 2008
  6. pmc A map of human protein interactions derived from co-expression of human mRNAs and their orthologs
    Arun K Ramani
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, TX, USA
    Mol Syst Biol 4:180. 2008
  7. pmc Human cell chips: adapting DNA microarray spotting technology to cell-based imaging assays
    Traver Hart
    Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, USA
    PLoS ONE 4:e7088. 2009
  8. pmc Age-dependent evolution of the yeast protein interaction network suggests a limited role of gene duplication and divergence
    Wan Kyu Kim
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS Comput Biol 4:e1000232. 2008
  9. pmc An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae
    Insuk Lee
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS ONE 2:e988. 2007
  10. pmc Transiently transfected purine biosynthetic enzymes form stress bodies
    Alice Zhao
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS ONE 8:e56203. 2013

Collaborators

Detail Information

Publications61

  1. ncbi request reprint Exploiting big biology: integrating large-scale biological data for function inference
    E Marcotte
    Department of Chemistry and Biochemistry and Institute for Cellular and Molecular Biology, University of Texas at Austin, 78712, USA
    Brief Bioinform 2:363-74. 2001
    ..This review discusses the most pertinent functional data for genome-wide functional inference and describes several methods by which these disparate data types are being integrated...
  2. pmc Systematic definition of protein constituents along the major polarization axis reveals an adaptive reuse of the polarization machinery in pheromone-treated budding yeast
    Rammohan Narayanaswamy
    Center for Systems and Synthetic Biology, Departments of Chemistry and Biochemistry, University of Texas, Austin, Texas 78712
    J Proteome Res 8:6-19. 2009
    ..The net effect is a defined ordering of major organelles along the polarization axis, with specific proteins implicated at the proximal growth tip...
  3. pmc Integrating shotgun proteomics and mRNA expression data to improve protein identification
    Smriti R Ramakrishnan
    Department of Computer Sciences, The University of Texas at Austin, Austin, TX 78712, USA
    Bioinformatics 25:1397-403. 2009
    ..However, there is often other information available, e.g. the probability of a protein's presence is likely to correlate with its mRNA concentration...
  4. pmc mspire: mass spectrometry proteomics in Ruby
    John T Prince
    Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA
    Bioinformatics 24:2796-7. 2008
    ..srf format), and modules for the calculation of peptide false identification rates...
  5. pmc Mechanisms of cell cycle control revealed by a systematic and quantitative overexpression screen in S. cerevisiae
    Wei Niu
    Center for Systems and Synthetic Biology, University of Texas, Austin, Texas, United States of America
    PLoS Genet 4:e1000120. 2008
    ..This work thus implicates new genes in cell cycle progression, complements previous screens, and lays the foundation for future experiments to define more precisely roles for these genes in cell cycle progression...
  6. pmc A map of human protein interactions derived from co-expression of human mRNAs and their orthologs
    Arun K Ramani
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, TX, USA
    Mol Syst Biol 4:180. 2008
    ..The new associations' derivation from conserved in vivo phenomena argues strongly for their biological relevance...
  7. pmc Human cell chips: adapting DNA microarray spotting technology to cell-based imaging assays
    Traver Hart
    Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, Texas, USA
    PLoS ONE 4:e7088. 2009
    ..The ability to prepare and store chips also allows researchers to follow up on observations gleaned from initial screens with maximal repeatability...
  8. pmc Age-dependent evolution of the yeast protein interaction network suggests a limited role of gene duplication and divergence
    Wan Kyu Kim
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS Comput Biol 4:e1000232. 2008
    ....
  9. pmc An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae
    Insuk Lee
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS ONE 2:e988. 2007
    ....
  10. pmc Transiently transfected purine biosynthetic enzymes form stress bodies
    Alice Zhao
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS ONE 8:e56203. 2013
    ....
  11. pmc A proteomic survey of widespread protein aggregation in yeast
    Jeremy D O'Connell
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, USA
    Mol Biosyst 10:851-61. 2014
    ..Thus, in yeast, the formation of stress bodies appears common across diverse, normally diffuse cytoplasmic proteins and is induced by multiple types of cell stress, including thermal, chemical, and nutrient stress. ..
  12. pmc Revisiting and revising the purinosome
    Alice Zhao
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA
    Mol Biosyst 10:369-74. 2014
    ..New discoveries challenge both the functional and physiological relevance of these bodies in favor of protein aggregation. ..
  13. pmc Prediction of gene-phenotype associations in humans, mice, and plants using phenologs
    John O Woods
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX 78712, USA
    BMC Bioinformatics 14:203. 2013
    ..Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes...
  14. pmc Inferring mouse gene functions from genomic-scale data using a combined functional network/classification strategy
    Wan Kyu Kim
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Speedway, Austin, Texas 78712, USA
    Genome Biol 9:S5. 2008
    ..The network and all predictions are available on the worldwide web...
  15. pmc How complete are current yeast and human protein-interaction networks?
    G Traver Hart
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712, USA
    Genome Biol 7:120. 2006
    ..Paradoxically, releasing raw, unfiltered assay data might help separate true from false interactions...
  16. pmc Broad network-based predictability of Saccharomyces cerevisiae gene loss-of-function phenotypes
    Kriston L McGary
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, Austin, Texas 78712, USA
    Genome Biol 8:R258. 2007
    ..To facilitate network-guided screens, a web server is available http://www.yeastnet.org...
  17. pmc Consolidating the set of known human protein-protein interactions in preparation for large-scale mapping of the human interactome
    Arun K Ramani
    Center for Systems and Synthetic Biology and Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA
    Genome Biol 6:R40. 2005
    ..To prepare for studies in humans, we wished to establish tests for the accuracy of future interaction assays and to consolidate the known interactions among human proteins...
  18. pmc A high-accuracy consensus map of yeast protein complexes reveals modular nature of gene essentiality
    G Traver Hart
    Center for Systems and Synthetic Biology Institute for Cellular and Molecular Biology University of Texas at Austin 2500 Speedway, Austin, Texas 78712, USA
    BMC Bioinformatics 8:236. 2007
    ..It is therefore useful to consider the raw data from each study and generate an accurate complex map from a high-confidence data set that integrates the results of these and earlier assays...
  19. pmc The APEX Quantitative Proteomics Tool: generating protein quantitation estimates from LC-MS/MS proteomics results
    John C Braisted
    Pathogen Functional Genomics Resource Center, J Craig Venter Institute, Rockville, MD 20850, USA
    BMC Bioinformatics 9:529. 2008
    ..This predicted spectral count is compared to the protein's observed MS total spectral count during APEX computation of protein abundances...
  20. pmc Disorder, promiscuity, and toxic partnerships
    Edward M Marcotte
    Department of Chemistry and Biochemistry, University of Texas at Austin, 2500 Speedway, Austin, TX 78712 1064, USA
    Cell 138:16-8. 2009
    ..Vavouri et al. (2009) find that intrinsic protein disorder and promiscuous molecular interactions are strong determinants of dosage sensitivity, explaining in part the toxicity of dosage-sensitive oncogenes in mice and humans...
  21. ncbi request reprint How do shotgun proteomics algorithms identify proteins?
    Edward M Marcotte
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, MBB 3 210, Austin, Texas 78712, USA
    Nat Biotechnol 25:755-7. 2007
  22. pmc Assembling a jigsaw puzzle with 20,000 parts
    Edward M Marcotte
    Department of Chemistry and Biochemistry and Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, Austin, TX 78712, USA
    Genome Biol 4:323. 2003
  23. doi request reprint A single gene network accurately predicts phenotypic effects of gene perturbation in Caenorhabditis elegans
    Insuk Lee
    Center for Systems and Synthetic Biology, Department of Chemistry and Biochemistry, Institute for Cellular and Molecular Biology, University of Texas, 2500 Speedway, MBB 3 210, Austin, Texas 78712, USA
    Nat Genet 40:181-8. 2008
    ..We conclude that an analogous network for human genes might be similarly predictive and thus facilitate identification of disease genes and rational therapeutic targets...
  24. ncbi request reprint Structural analysis shows five glycohydrolase families diverged from a common ancestor
    J D Robertus
    Department of Chemistry and Biochemistry, University of Texas, Austin 78712, USA
    J Exp Zool 282:127-32. 1998
    ..The eucaryotes have a small N terminal domain, while the procaryotes have none. The C terminal domain of the eucaryotic family contains a single alpha-helix, while the prokaryotic domain has three antiparallel helices...
  25. pmc Sequence signatures and mRNA concentration can explain two-thirds of protein abundance variation in a human cell line
    Christine Vogel
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78229 3900, USA
    Mol Syst Biol 6:400. 2010
    ....
  26. pmc It's the machine that matters: Predicting gene function and phenotype from protein networks
    Peggy I Wang
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712 1064, USA
    J Proteomics 73:2277-89. 2010
    ....
  27. pmc Mining gene functional networks to improve mass-spectrometry-based protein identification
    Smriti R Ramakrishnan
    Department of Computer Sciences, 1 University Station C0500, The University of Texas at Austin, Austin, TX 78712, USA
    Bioinformatics 25:2955-61. 2009
    ..However, there is often other evidence to suggest that a protein is present and confidence in individual protein identification can be updated accordingly...
  28. ncbi request reprint Calculating absolute and relative protein abundance from mass spectrometry-based protein expression data
    Christine Vogel
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, 2500 Speedway, MBB 3 210, Austin, Texas 78712, USA
    Nat Protoc 3:1444-51. 2008
    ..e., measuring relative protein abundances. APEX-based protein abundances span 3-4 orders of magnitude and are applicable to mixtures of 100s to 1,000s of proteins...
  29. ncbi request reprint Integrating functional genomics data
    Insuk Lee
    Center for Systems and Synthetic Biology, Institute for Molecular Biology, University of Texas at Austin, Austin, TX, USA
    Methods Mol Biol 453:267-78. 2008
    ..The approach is easily applied to multicellular organisms, including human...
  30. ncbi request reprint Absolute protein expression profiling estimates the relative contributions of transcriptional and translational regulation
    Peng Lu
    Center for Systems and Synthetic Biology, Department of Chemistry and Biochemistry, Institute for Cellular and Molecular Biology, 2500 Speedway, University of Texas, Austin, Texas 78712, USA
    Nat Biotechnol 25:117-24. 2007
    ..Therefore, levels of both eukaryotic and prokaryotic proteins are set per mRNA molecule and independently of overall protein concentration, with >70% of yeast gene expression regulation occurring through mRNA-directed mechanisms...
  31. ncbi request reprint Comparative experiments on learning information extractors for proteins and their interactions
    Razvan Bunescu
    Department of Computer Sciences, University of Texas, Austin, TX 78712, USA
    Artif Intell Med 33:139-55. 2005
    ..We have developed and evaluated a variety of learned information extraction systems for identifying human protein names in Medline abstracts and subsequently extracting information on interactions between the proteins...
  32. ncbi request reprint A probabilistic functional network of yeast genes
    Insuk Lee
    Center for Systems and Synthetic Biology, Institute for Molecular Biology, University of Texas at Austin, Austin, TX 78712 1064, USA
    Science 306:1555-8. 2004
    ..The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis...
  33. ncbi request reprint A fast coarse filtering method for peptide identification by mass spectrometry
    Smriti R Ramakrishnan
    Department of Computer Sciences, The University of Texas at Austin Austin, Texas 78712, USA
    Bioinformatics 22:1524-31. 2006
    ..Our search method leverages a metric space indexing algorithm to produce an initial candidate set, which can be followed by any fine ranking scheme...
  34. ncbi request reprint The need for a public proteomics repository
    John T Prince
    Center for Systems and Synthetic Biology and Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas 78712, USA
    Nat Biotechnol 22:471-2. 2004
  35. pmc Ribosome stalk assembly requires the dual-specificity phosphatase Yvh1 for the exchange of Mrt4 with P0
    Kai Yin Lo
    Department of Chemistry and Biochemistry, Section of Molecular Genetics and Microbiology, The Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA
    J Cell Biol 186:849-62. 2009
    ..The initial assembly of the ribosome with Mrt4 may provide functional compartmentalization of ribosome assembly in addition to the spatial separation afforded by the nuclear envelope...
  36. ncbi request reprint Protein function prediction using the Protein Link EXplorer (PLEX)
    Shailesh V Date
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, 1 University Station, A4800, Austin, TX 78712 1064, USA
    Bioinformatics 21:2558-9. 2005
    ..AVAILABILITY: http://bioinformatics.icmb.utexas.edu/plex..
  37. ncbi request reprint Discovery of uncharacterized cellular systems by genome-wide analysis of functional linkages
    Shailesh V Date
    Center for Computational Biology and Bioinformatics, Institute for Cellular and Molecular Biology, 1 University Station A4800, Austin, Texas 78712 1064, USA
    Nat Biotechnol 21:1055-62. 2003
    ..The search of such networks for groups of uncharacterized, linked proteins led to the identification of 27 novel cellular systems from one nonpathogenic and three pathogenic bacterial genomes...
  38. ncbi request reprint LGL: creating a map of protein function with an algorithm for visualizing very large biological networks
    Alex T Adai
    Center for Systems and Synthetic Biology, and Institute for Cellular and Molecular Biology, 1 University Avenue, University of Texas, Austin, TX 78712 1095, USA
    J Mol Biol 340:179-90. 2004
    ..Using the map produced by LGL, we infer general functions for 23 uncharacterized protein families...
  39. ncbi request reprint Exploiting the co-evolution of interacting proteins to discover interaction specificity
    Arun K Ramani
    Institute for Cellular and Molecular Biology, Center for Computational Biology and Bioinformatics, University of Texas at Austin, Austin, TX 78712, USA
    J Mol Biol 327:273-84. 2003
    ..Using these methods, it is possible to successfully find protein interaction specificities, as demonstrated for >18 protein families...
  40. pmc Buffering by gene duplicates: an analysis of molecular correlates and evolutionary conservation
    Kevin Hannay
    Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, University of Texas at Austin, 2500 Speedway, MBB 3 210, Austin, TX 78712, USA
    BMC Genomics 9:609. 2008
    ....
  41. doi request reprint Effects of functional bias on supervised learning of a gene network model
    Insuk Lee
    Center of Systems and Synthetic Biology, Institute for Molecular Biology, University of Texas at Austin, Austin, TX, USA
    Methods Mol Biol 541:463-75. 2009
    ..This suggests that careful use of current knowledge and genomics data is required for successful gene network modeling using the supervised learning approach. We provide guidance for better use of these data in learning gene networks...
  42. pmc Rational extension of the ribosome biogenesis pathway using network-guided genetics
    Zhihua Li
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas, USA
    PLoS Biol 7:e1000213. 2009
    ....
  43. ncbi request reprint Predicting functional linkages from gene fusions with confidence
    Cynthia J Verjovsky Marcotte
    Department of Mathematics, St Edwards University, Austin, Texas 78712, USA
    Appl Bioinformatics 1:93-100. 2002
    ..Using the Rosetta Stone method and this scoring scheme, we find all significant functional linkages for proteins of E. coli, P. horikshii and S. cerevisiae, and measure the extent of the resulting protein networks...
  44. pmc Systematic profiling of cellular phenotypes with spotted cell microarrays reveals mating-pheromone response genes
    Rammohan Narayanaswamy
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, 2500 Speedway, University of Texas, Austin, TX 78712, USA
    Genome Biol 7:R6. 2006
    ..Besides morphology assays, cell microarrays should be valuable for high-throughput in situ hybridization and immunoassays, enabling new classes of genetic assays based on cell imaging...
  45. ncbi request reprint Global metabolic changes following loss of a feedback loop reveal dynamic steady states of the yeast metabolome
    Peng Lu
    Center for Systems and Synthetic Biology, University of Texas, 1 University Station, Austin, TX 78712 0159, USA
    Metab Eng 9:8-20. 2007
    ..Global metabolic changes are not necessarily accompanied by global transcriptional changes, and metabolite-controlled post-transcriptional regulation of metabolic enzymes is clearly evident...
  46. pmc Bud23 methylates G1575 of 18S rRNA and is required for efficient nuclear export of pre-40S subunits
    Joshua White
    Section of Molecular Genetics and Microbiology, 1 University Station, A5000, The University of Texas at Austin, Austin, TX 78712 0162, USA
    Mol Cell Biol 28:3151-61. 2008
    ..Thus, Bud23 protein, but not its methyltransferase activity, is important for biogenesis and export of the 40S subunit in yeast...
  47. ncbi request reprint Diametrical clustering for identifying anti-correlated gene clusters
    Inderjit S Dhillon
    Department of Computer Sciences, Institute for Cellular and Molecular Medicine, University of Texas, Austin, TX 78712, USA
    Bioinformatics 19:1612-9. 2003
    ..Biologically, this is not unintuitive-genes responding to the same stimuli, regardless of the nature of the response, are more likely to operate in the same pathways...
  48. pmc Defining the pathway of cytoplasmic maturation of the 60S ribosomal subunit
    Kai Yin Lo
    Section of Molecular Genetics and Microbiology, University of Texas at Austin, Austin, TX 78712, USA
    Mol Cell 39:196-208. 2010
    ..Finally, the release of Tif6 is a prerequisite for the release of the nuclear export adaptor Nmd3. Establishing this pathway provides an important conceptual framework for understanding ribosome maturation...
  49. ncbi request reprint Chromatographic alignment of ESI-LC-MS proteomics data sets by ordered bijective interpolated warping
    John T Prince
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA
    Anal Chem 78:6140-52. 2006
    ..Using optimized parameters, we show that OBI-Warp produces alignments consistent with time standards across these data sets. The source and executables are released under MIT style license at http://obi-warp.sourceforge.net/...
  50. pmc Systematic discovery of nonobvious human disease models through orthologous phenotypes
    Kriston L McGary
    Department of Molecular Cell and Developmental Biology, Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, TX 78712, USA
    Proc Natl Acad Sci U S A 107:6544-9. 2010
    ..Phenologs reveal functionally coherent, evolutionarily conserved gene networks-many predating the plant-animal divergence-capable of identifying candidate disease genes...
  51. pmc Mass spectrometry of the M. smegmatis proteome: protein expression levels correlate with function, operons, and codon bias
    Rong Wang
    Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, and Department of Chemistry and Biochemistry, University of Texas at Austin, Austin, Texas 78712, USA
    Genome Res 15:1118-26. 2005
    ....
  52. pmc Expression deconvolution: a reinterpretation of DNA microarray data reveals dynamic changes in cell populations
    Peng Lu
    Department of Chemistry and Biochemistry, Center for Computational Biology and Bioinformatics, 1 University Station, A4800, University of Texas, Austin, TX 78712 0159, USA
    Proc Natl Acad Sci U S A 100:10370-5. 2003
    ..Expression deconvolution allows a reinterpretation of the cell cycle dynamics underlying all previous microarray experiments and can be more generally applied to study most forms of cell population dynamics...
  53. pmc Group II intron protein localization and insertion sites are affected by polyphosphate
    Junhua Zhao
    Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, Texas, United States of America
    PLoS Biol 6:e150. 2008
    ....
  54. pmc The planar cell polarity effector Fuz is essential for targeted membrane trafficking, ciliogenesis and mouse embryonic development
    Ryan S Gray
    Dept of Molecular Cell and Developmental Biology, Institute for Cellular and Molecular Biology, University of Texas, Austin, Texas 78712, USA
    Nat Cell Biol 11:1225-32. 2009
    ..These results are significant because they provide new insights into the mechanisms by which developmental regulatory systems such as PCP signalling interface with fundamental cellular systems such as the vesicle trafficking machinery...
  55. doi request reprint The proteomic response of Mycobacterium smegmatis to anti-tuberculosis drugs suggests targeted pathways
    Rong Wang
    Center for Systems and Synthetic Biology, Institute of Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA
    J Proteome Res 7:855-65. 2008
    ..We identify proteins involved in target pathways for the three drugs and infer putative targets for 5-chloropyrazinamide...
  56. pmc Widespread reorganization of metabolic enzymes into reversible assemblies upon nutrient starvation
    Rammohan Narayanaswamy
    Department of Chemistry and Biochemistry, University of Texas, Institute for Cellular and Molecular Biology, Center for Systems and Synthetic Biology, Austin, TX 78712 1064, USA
    Proc Natl Acad Sci U S A 106:10147-52. 2009
    ..Thus, upon nutrient depletion we observe widespread protein assemblies displaying nutrient-specific formation and dissolution...
  57. ncbi request reprint A probabilistic view of gene function
    Andrew G Fraser
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK
    Nat Genet 36:559-64. 2004
    ..Even this comprehensive view fails to capture key aspects of gene function, not least their dynamics in time and space, showing that there are limitations to the model that must ultimately be addressed...
  58. pmc A critical assessment of Mus musculus gene function prediction using integrated genomic evidence
    Lourdes 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...
  59. ncbi request reprint Protein interaction networks from yeast to human
    Peer Bork
    European Molecular Biology Laboratory, Structural and Computational Biology Programme, Meyerhofstrasse 1, 69117 Heidelberg, Germany
    Curr Opin Struct Biol 14:292-9. 2004
    ....
  60. ncbi request reprint Synthetic biology: engineering Escherichia coli to see light
    Anselm Levskaya
    Biophysics Program, University of California, San Francisco, California 94143, USA
    Nature 438:441-2. 2005
    ..This spatial control of bacterial gene expression could be used to 'print' complex biological materials, for example, and to investigate signalling pathways through precise spatial and temporal control of their phosphorylation steps...
  61. ncbi request reprint Development through the eyes of functional genomics
    Andrew G Fraser
    Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
    Curr Opin Genet Dev 14:336-42. 2004
    ....

Research Grants13

  1. Reconstructing the eukaryotic cell cycle gene network
    Edward Marcotte; Fiscal Year: 2004
    ..abstract_text> ..
  2. Cell chips for genome-wide protein and RNA localization in single cells
    Edward Marcotte; Fiscal Year: 2009
    ..This work will increase our understanding of the mechanisms and circumstances under which proteins aggregate, and thus will be a step towards better understanding of the forces underlying aggregation diseases and aging. ..
  3. Network-directed discovery of disease genes
    Edward M Marcotte; Fiscal Year: 2010
    ..This work will increase our understanding of the genetic basis of neural tube birth defects and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases. ..
  4. Systematic discovery of nonobvious human disease models by orthologous phenotypes
    Edward Marcotte; Fiscal Year: 2009
    ..More generally, this work will increase our understanding of the genetic basis of polygenic diseases and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases. ..
  5. Network-directed discovery of disease genes
    Edward Marcotte; Fiscal Year: 2009
    ..This work will increase our understanding of the genetic basis of neural tube birth defects and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases. ..
  6. Cell chips for genome-wide protein and RNA localization in single cells
    Edward Marcotte; Fiscal Year: 2009
    ..abstract_text> ..
  7. Cell chips for genome-wide protein and RNA localization in single cells
    Edward Marcotte; Fiscal Year: 2007
    ....
  8. Reconstructing the eukaryotic cell cycle gene network
    Edward Marcotte; Fiscal Year: 2007
    ..abstract_text> ..
  9. Reconstructing the eukaryotic cell cycle gene network
    Edward Marcotte; Fiscal Year: 2006
    ..abstract_text> ..
  10. Cell chips for genome-wide protein and RNA localization in single cells
    Edward Marcotte; Fiscal Year: 2006
    ....
  11. Reconstructing the eukaryotic cell cycle gene network
    Edward Marcotte; Fiscal Year: 2005
    ..abstract_text> ..
  12. Systematic discovery of nonobvious human disease models by orthologous phenotypes
    Edward M Marcotte; Fiscal Year: 2010
    ..More generally, this work will increase our understanding of the genetic basis of polygenic diseases and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases. ..