Krishna Karuturi, Ph.D.
Director, Computational Sciences
Computational Cancer Biology, Statistical Bioinformatics, Network Biology and Predictive Genomic Medicine
Computational Cancer Biology, Statistical Bioinformatics, Network Biology and Predictive Genomic Medicine
My primary responsibility is to direct R&D operations of Computational Sciences (CS) at The Jackson Laboratory. CS works with our collaborators and partners at all campuses of The Jackson Laboratory and the expertise of CS spans the whole landscape of bioinformatics.
My research interests are in developing and applying statistical bioinformatics methods, machine learning algorithms and network biology approaches to understand disease biology and model biological processes such as cell division cycle and DNA replication. We mine integrative heterogeneous omics data analysis and modeling as basis for our research.
Krishna Karuturi on Google Scholar
Krishna Karuturi on Researchgate
Nathan Lawler, Alec Fabbri, Peiyong Guan, Joshy George and R. Krishna Murthy Karuturi, multiClust: An R-package for identifying biologically relevant clusters in cancer transcriptome profiles. Cancer Informatics, 2016 Jun; 15:103-114
Juntao Li, Lei Zhu, Eshaghi Majid, Jianhua Liu and R. Krishna Murthy Karuturi, Deciphering DNA-protein interaction patterns from High-density ChIP-chip data, BMC Proceedings. 2011;5:S2.
Guruprasad Ananda, Susan Mockus, Micaela Lundquist, Vanessa Spotlow, Al Simons, Talia Mitchell, Grace Stafford, Vivek Philip, Timothy Stearns, Anuj Srivastava, Mary Barter, Lucy Rowe, Joan Malcolm, Carol Bult, Radha Krishna Murthy Karuturi, Karen Rasmussen and Douglas Hinerfeld, Development and validation of the JAX Cancer Treatment Profile™ for detection of clinically actionable mutations in solid tumors, Experimental and Molecular Pathology, 2015.
Luo H, Li J, Eshaghi M, Liu J, Karuturi RKM Genome-wide estimation of firing efficiencies of origins of DNA replication from time-course copy number variation data, BMC Bioinformatics. 2010;11(1):247.
Sigrid Rouam, Lance D Miller, R Krishna Murthy Karuturi, Identifying Driver Genes in Cancer by Triangulating Gene Expression, Gene Location, and Survival Data, Cancer Informatics. 2014 December.
Haixia Li and R. Krishna Murthy Karuturi, Significance Analysis and Improved Discovery of Disease Specific Differentially Co-expressed Gene Sets in Microarray Data, Intl Jl of Datamining and Bioinformatics, 4(6):617-638, 2010
Koichiro Inaki, Francesca Menghi, Xing Yi Woo, Joel P. Wagner, Pierre-Étienne Jacques, Yi Fang Lee, Phung Trang Shreckengast, Wendy WeiJia Soon, Ankit Malhotra, Audrey S.M. Teo, Axel M. Hillmer, Alexis Jiaying Khng, Xiaoan Ruan, Swee Hoe Ong, Denis Bertrand, Niranjan Nagarajan, R. Krishna Murthy Karuturi, Alfredo Hidalgo Miranda, and Edison T. Liu, Systems consequences of amplicon formation in human breast cancer, Genome Res. 2014 October; 24:1559-1571.
Francesca Menghi, Koichiro Inaki, XingYi Woo, Pooja A Kumar, Krzysztof R Grzeda, Ankit Malhotra, Vinod Yadav, Hyunsoo Kim, Eladio J Marquez, Duygu Ucar, Phung T Shreckengast, Joel P Wagner, George MacIntyre, Krishna R Murthy Karuturi, Ralph Scully, James Keck, Jeffrey H. Chuang, Edison T. Liu. The Tandem Duplicator Phenotype as a distinct genomic configuration in cancer. PNAS. 2016 April; 113(7).
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