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Reconstruction of Pathways Associated with Amino Acid Metabolism in Human Mitochondria

Genomics, Proteomics & Bioinformatics 2007年第3期5卷 166-176页

作者： purnima guda Chittibabu guda Shankar Subramaniam Gen *NY* sis Center for Excellence in Cancer Genomics and Department of Epidemiology and Biostatistics State University of New York at AlbanyRensselaerNY 12144-3456USA San Diego Supercomputer Center University of California at San DiegoLa JollaCA 92093-0505USA Departments of BioengineeringChemistry and BiochemistryUniversity of California at San DiegoLa JollaCA 92093USA.

We have used a bioinformatics approach for the identification and reconstruction of metabolic pathways associated with amino acid metabolism in human mitochondria. Human mitochondrial proteins determined by experimental and computational methods have been superposed on the reference pathways from the KEGG database to identify mitochondrial pathways. Enzymes at the entry and exit points for each reconstructed pathway were identified, and mitochondrial solute carrier proteins were determined where applicable. Intermediate enzymes in the mitochondrial pathways were identified based on the annotations available from public databases, evidence in current literature, or our MITOPRED program, which predicts the mitochondrial localization of proteins. Through integration of the data derived from experimental, bibliographical, and computational sources, we reconstructed the amino acid metabolic pathways in human mitochondria, which could help better understand the mitochondrial metabolism and its role in human health.

关键词： mitochondria metabolic pathways amino acid metabolism human

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Comparative Analysis of Protein-Protein Interactions in Cancer-Associated Genes

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Genomics, Proteomics & Bioinformatics 2009年第1期7卷 25-36页

作者： purnima guda Sridar V. Chittur Chittibabu guda GenNYsis Center for Excellence in Cancer Genomics and Department of Epidemiology & Biostatistics State University of New York at AlbanyRensselaer NY 12144-3456 USA Center for Functional Genomics and Department of Biomedical Sciences State University of New York at AlbanyRensselaer NY 12144-3456 USA

Protein-protein interactions （PPIs） have been widely studied to understand the biological processes or molecular functions associated with different disease systems like cancer. While focused studies on individual cancers have generated valuable information, global and comparative analysis of datasets from different cancer types has not been done. In this work, we carried out bioinformatic analysis of PPIs corresponding to differentially expressed genes from microarrays of various tumor tissues （belonging to bladder, colon, kidney and thyroid cancers） and compared their associated biological processes and molecular functions （based on Gene Ontology terms）. We identified a set of processes or functions that are common to all these cancers, as well as those that are specific to only one or partial cancer types. Similarly, protein interaction networks in nucleic acid metabolism were compared to identify the common/specific clusters of proteins across different cancer types. Our results provide a basis for further experimental investigations to study protein interaction networks associated with cancer. The methodology developed in this work can also be applied to study similar disease systems.

关键词： protein-protein interaction,cancer-associated genes GO similarity analysis cancer bioinformatics

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