Integrating Evolving Tools for Proteomics Research

Havre, Susan L; Singhal, Mudita; Gopalan, Banu; Payne, Deborah A; Klicker, Kyle R; Kiebel, Gary R; Auberry, Kenneth J; Stephan, Eric G; Webb-Robertson, Bobbie-Jo M; Gracio, Deborah K

Title: Integrating Evolving Tools for Proteomics Research

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Abstract

The recent development of high-throughput proteomics techniques has resulted in the exponential growth of experimental proteomics data. At the same time, the amount of published biological information—which includes not only journal articles but also gene sequences, annotations, and biological ontologies—is also growing rapidly. To extract information from these large, diverse data sets, biologists will require powerful data management, analysis, and integration tools. More than that, biologists will need these diverse tools integrated into a computational environment that allows them to focus on the science. Without an integrated environment, biologists must attend to non-scientific tasks, for example, moving data files or altering data formats; such tasks can be a nuisance with small data sets and significant obstacles with large data sets. This paper explores an integrated computational environment for proteomics by loosely connecting individual components for data storage, retrieval, analysis, and visualization.

Authors:: Havre, Susan L; Singhal, Mudita; Gopalan, Banu; Payne, Deborah A; Klicker, Kyle R; Kiebel, Gary R; Auberry, Kenneth J; Stephan, Eric G; Webb-Robertson, Bobbie-Jo M; Gracio, Deborah K

Publication Date:: Wed Jun 23 00:00:00 EDT 2004

Research Org.:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 15009514

Report Number(s):: PNNL-SA-40933
TRN: US200428%%1105

DOE Contract Number:: AC05-76RL01830

Resource Type:: Conference

Resource Relation:: Conference: Proceedings of The 2004 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences, 2004:307-313

Country of Publication:: United States

Language:: English

Subject:: 99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; GENES; MANAGEMENT; MEDICINE; STORAGE; proteomics, information management, problem solving environment, visualization

Citation Formats


                    Havre, Susan L, Singhal, Mudita, Gopalan, Banu, Payne, Deborah A, Klicker, Kyle R, Kiebel, Gary R, Auberry, Kenneth J, Stephan, Eric G, Webb-Robertson, Bobbie-Jo M, and Gracio, Deborah K. Integrating Evolving Tools for Proteomics Research.  United States: N. p., 2004. 
        Web.

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                    Havre, Susan L, Singhal, Mudita, Gopalan, Banu, Payne, Deborah A, Klicker, Kyle R, Kiebel, Gary R, Auberry, Kenneth J, Stephan, Eric G, Webb-Robertson, Bobbie-Jo M, & Gracio, Deborah K. Integrating Evolving Tools for Proteomics Research.  United States.

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                    Havre, Susan L, Singhal, Mudita, Gopalan, Banu, Payne, Deborah A, Klicker, Kyle R, Kiebel, Gary R, Auberry, Kenneth J, Stephan, Eric G, Webb-Robertson, Bobbie-Jo M, and Gracio, Deborah K. 2004.  
        "Integrating Evolving Tools for Proteomics Research".  United States.

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@article{osti_15009514,

  title        = {Integrating Evolving Tools for Proteomics Research},

  author       = {Havre, Susan L and Singhal, Mudita and Gopalan, Banu and Payne, Deborah A and Klicker, Kyle R and Kiebel, Gary R and Auberry, Kenneth J and Stephan, Eric G and Webb-Robertson, Bobbie-Jo M and Gracio, Deborah K},

  abstractNote = {The recent development of high-throughput proteomics techniques has resulted in the exponential growth of experimental proteomics data. At the same time, the amount of published biological information—which includes not only journal articles but also gene sequences, annotations, and biological ontologies—is also growing rapidly. To extract information from these large, diverse data sets, biologists will require powerful data management, analysis, and integration tools. More than that, biologists will need these diverse tools integrated into a computational environment that allows them to focus on the science. Without an integrated environment, biologists must attend to non-scientific tasks, for example, moving data files or altering data formats; such tasks can be a nuisance with small data sets and significant obstacles with large data sets. This paper explores an integrated computational environment for proteomics by loosely connecting individual components for data storage, retrieval, analysis, and visualization.},

  doi          = {},

  url          = {https://www.osti.gov/biblio/15009514},
  journal      = {},
number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Jun 23 00:00:00 EDT 2004},

  month        = {Wed Jun 23 00:00:00 EDT 2004}

}

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