Dr. Babu Guda
Assistant Dean for Research Development, College of Medicine
Professor & Vice Chair, Department of Genetics, Cell Biol. & Anatomy
Co-Director, Center for Biomedical Informatics Research & Innovation
Director, Bioinformatics and Systems Biology Core
Fellow, National Stragegic Research Institute (NSRI), a DoD-designated UARC
University of Nebraska Medical Center, Omaha, NE 68198-5805
Phone: (402) 559-5954
I have been a life-long learner and pursuer of interdisciplinary knowledge. This trait has shaped my career in an unconventional way. I started off my Bachelors degree in agricultural sciences and kept changing fields as I collected more degrees with a Masters degree in Genetics, PhD in molecular Biology, computer science, and computational biology during my post-doctoral training, and finally carving out a career as a bioinformatician. My current research interests are in the areas of computational biology, systems biology, cancer genomics and precision medicine. I use machine learning and artificial intelligence (AI) approaches to develop computational solutions to biological problems.
Im a tenured Professor and Assistant Dean for Research Development at the College of Medicine, University of Nebraska Medical Center (UNMC). I have over 25 years of experience in biomedical research, bioinformatics teaching and mentoring, research resource development and academic administration. Im the founding director of the Bioinformatics and Systems Biology (BSB) Core facility at UNMC, which provides bioinformatics support for hundreds of investigators across Nebraska and neighboring states. Over the past 20 years, Ive mentored over 50 mentees in my laboratory, including 15 PhD students, 10 postdocs and 9 junior faculty, and have published over 120 peer-reviewed research articles. My team has developed over a dozen novel algorithms and bioinformatics software tools. I have served as a member of NIH grant review panels, editorial boards of research journals, and external advisory boards of NIH program projects. Im also the inaugural Co-Director of the Center for Biomedical Informatics Research and Innovation that was recently approved by the NU Board of Regents as a joint center of UNMC and UNO.
Southekal S, Mishra NK, Guda C. (2021) Pan-cancer analysis of human kinome gene expression and promoter DNA methylation identifies prognostic biomarkers in multiple cancers. Cancers 13:1189. PMID: 33801837
Vellichirammal NN, Albahrani A, Banwait JK, Mishra NK, Li Y, Roychoudhury S, King MJ, Mirza S, Bhakat KK, Band V, Joshi SS, Guda C. (2020) Pan-cancer analysis reveals the diverse landscape of novel sense and antisense fusion transcripts. Molecular Therapy Nucleic Acids, 19:1379-98. PMID: 32160708
Mishra NK, Meng N, Guda C. (2020) Identification of prognostic markers in cholangiocarcinoma using altered DNA methylation and gene expression profiles. Frontiers in Genetics, 11:522125. PMID: 33193605
Bahado-Singh R, Vishweswaraiah S, Aydas B, Mishra NK, Yilmaz A, Guda C, Radhakrishna U. (2019) Artificial intelligence analysis of Newborn Leucocyte epigenomic markers for the Prediction of Autism, Brain Research, 1724:146457, PMID: 31521637
Li Y, Heavican TB, Vellichirammal NN, Iqbal J, Guda C. (2017) ChimeRScope: a novel alignment-free algorithm for fusion gene prediction using paired-end RNA-Seq data, Nucleic Acids Res. 45:e120. PMID: 28472320
Vural S, Wang X, Guda C. (2016) Classification of breast cancer patients using somatic mutation profiles and machine learning approaches, BMC Systems Biology 10 Suppl 3:62. PMID: 27587275
Mohammed A, Guda C. (2015) Application of a hierarchical enzyme classification method reveals the role of gut microbiome in human metabolism. BMC Genomics, Suppl 7:S16. PMID: 26099921
King BR, Guda C (2008) Semi-supervised learning for classification of protein sequence data. Scientific Programming, 16:5-29.
King B, Guda C. (2007) ngLOC: An n-gram based Bayesian method for estimating the subcellular proteomes of eukaryotes. Genome Biology, 8:R68.
Guda C, Scheeff ED, Bourne PE, Shindyalov IN. (2001) A new algorithm for the alignment of multiple protein structures using Monte Carlo optimization. Proc. of the Pacific Symposium on Biocomputing, pp.275-286