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Pathways Analysis using Protein Expression Data

Pathways Analysis using Protein Expression Data . Venkatesh Jitender (vjk@cbmi.upmc.edu) Dr. Vanathi Gopalakrishnan Center for Biomedical Informatics, UPMC. Bio-Chemical Pathways & Protein Expression Profiles.

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Pathways Analysis using Protein Expression Data

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  1. Pathways Analysis using Protein Expression Data Venkatesh Jitender (vjk@cbmi.upmc.edu) Dr. Vanathi Gopalakrishnan Center for Biomedical Informatics, UPMC

  2. Bio-Chemical Pathways & Protein Expression Profiles • Organisms function through intricate networks of chemical reactions and interacting molecules. • Metabolic Pathway • Can be thought of as a “state representation” network • Regulatory Pathway: • Can be thought of as a “switch activating or de-activating” diagram Protein Expression Profiles: • Mass- spectrometry • Protein Array technology, etc.

  3. Suite of Databases and Associated Software http://www.genome.ad.jp/kegg/kegg2.html#pathway Includes : PATHWAY database GENES & PROTEINS (Genes / SSD / KO databases) CHEMICAL COMPOUNDS & REACTIONS (Compound / Reaction database) Statistics: Number of pathways10,677(PATHWAY database) Number of reference pathways226(PATHWAY database) KEGG Database:

  4. Metabolic Pathway:

  5. Regulatory Pathway:

  6. Proposal: • Identify co- relation between observed protein expression profiles and Biochemical Pathways. • Provide an online web-service to predict the “Most-Probable” pathway • Rank putative pathways based on Activity score: analyze difference in expression profiles Co regulation score: analyze similarity in expression profiles within a pathway Cascade score: analyze structure, measuring activity and coregulation

  7. Project Architecture Putative Pathway Set Application Server KEGG Server KEGG API Analysis Routine get_pathway_by_enzyme Recommended Pathway User submits sequence data

  8. Analysis Routine Application Server • Analysis Routine • Score Pathway based on: • Activity • Coregulation • Cascade Suggested Pathway Putative Pathway Set

  9. Implementation Details • Option of program being hosted public (server) / standalone application • Application server: JAVA servlets, JSP • Analysis Routine: C/ JAVA • Messaging System: HTTP • Communication Protocol: SOAP (xml format)

  10. Applications: • Pathway knowledge helpful in: • Deeper understanding of cell mechanisms under various conditions • Predict possible drug targets, • Provide end- user on most probable pathway set, from a publicly available database

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