Raja Mazumder, PhD
Affiliation: Cancer Biology Research Program, Biochemistry and Molecular Medicine
Researcher Bio:

Dr. Mazumder is a Professor of Biochemistry and Molecular Medicine and Co-Director of The McCormick Genomic Proteomic Center at The George Washington University (GW). His background is in evolutionary biology and bioinformatics. He has worked at Oak Ridge National Laboratory, Merck, NIH, and Georgetown University before coming to GW. While working at National Center for Biotechnology Information (NCBI) at NIH, UniProt and Protein Information Resource (PIR), Dr. Mazumder worked closely with colleagues in developing international molecular biology resources and using these resources to identify therapeutics, diagnostics and vaccines targets. Through NIH, NSF, FDA and industry funding he is involved in genomic and bioinformatics research in cancer biology, glycobiology, metagenomics and bioinformatics standards development. Dr. Mazumder leads the public High Performance Integrated Virtual Environment (HIVE). HIVE is approved for use in a regulatory environment at US FDA. In addition to his research activities he mentors PhD and MS students and co-directs the Bioinformatics M.S. graduate program track and Genomics and Bioinformatics PhD program at GW.

Research Summary:

Applied bioinformatics and computational biochemistry strongly rooted in evolutionary biology form the basis of my research program. Many of our bioinformatics predictions have been validated in the laboratory, and there are currently a few that are in the wet-lab testing phase. Our current research goals includes conducting a comprehensive comparative analysis at the genomic level, the development of methods to perform analysis of extra-large data sets (such as next generation data and proteomics data) within the context of evolutionary systems biology to identify experimental therapeutic targets, and to create a bioinformatics data-warehouse for “omics” data integration for cancer research. We use bioinformatic approaches in conjunction with experimental data to identify potential experimental targets for development of diagnostics/therapeutics. Our objective is to perform predictive modeling of cancer pathways, systems-level evolutionary analysis of genes, proteins and their regulation, spanning major oncovirus pathogen groups. Ongoing research includes development of High-performance Integrated Virtual Environment (HIVE), a cloud-based environment that contains various bio-scientific tools for analysis of extra-large data; identification of vaccine and therapeutic targets for Hepatitis C Virus; identification of non-synonymous Single Nucleotide Variations (nsSNV) that affect post-translational modifications and their relationship to cancer and other diseases. Visit the Mazumder Lab website.

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Research Interests: Computational Biochemistry, Bioinformatics, Genomics, Proteomics