Journal of Data Mining in Genomics & Proteomics

Hima Yalamanchili

Hima Yalamanchili, Ph.D
Executive Editor
Executive Editor, Genomic Analysis
Wright State University, USA

Biography

Post-Doctoral Fellow, Biogen- Massachusetts

Omics data analysis
Execute and analyze complex data, compare tens of thousands of gene transcripts, protein levels, etc. across multiple processes and cell lines, advanced biological conclusions

Doctor of Philosophy, Biomedical Sciences (Concentration in Bioinformatics)                                           2018
Wright State University, USA

Master of Science, Cellular & Structural Biology                                                                                        2010
The University of Texas Health Science Center at San Antonio, USA

Research Interest

Computational discovery of novel genes in breast cancer and melanoma.

Developed a pipeline using text mining and mathematical models that allows to identify and interpret genetic markers for breast cancer based on gene expression data with over 90% accuracy in a cost-effective manner. Identified and characterized these genes using R, python and MATLAB and pathway analysis. Investigated the effect of copy number variation on melanoma classification and significantly reduced misdiagnosis of melanoma from benign melanocytic nevi.

Application of topological data analysis for identification of novel melanoma subtypes

Identified a sub-class of melanoma that exhibits 100% survival and no metastasis using a topology-based method that extracts information from copy number data and SNP data and, by using topology, provides greater depth of information than current analytic techniques