Informatics and Systems Biology of Complex Disease. The computational challenges of studying complex diseases, such as cancer, neurological disorders, diabetes, and deadly infections, are diverse and range from gathering biomedical data to determining the key molecular mechanisms behind the disease, from understanding the dynamics of the molecular system during the disease onset to making accurate predictions on the clinical outcomes. Our research in this area integrates the next-generation sequencing, structural genomics, and interactomics data and leverages state-of-the-art computational paradigms, such as deep learning, semi-supervised learning and agent-based systems. We are also working in collaboration with experimental labs to study specific diseases in human, animals, and plants.
Biomedical Data Analytics and Visualization. We are developing computational methods for fast collection and processing of the large-scale biomedical datasets. Current projects include mining macromolecular interaction and genetic variation data and organizing it into a comprehensive database, mixed reality visualization and manipulation of massive datasets, as well as developing deep clustering approaches for transcriptomics analysis.
Computational Genomics. Advances in computational genomics have the potential to greatly benefit evolutionary and regulatory genomics. We employ algorithms driven by biological phenomena to determine important functional and structural elements of the genome and trace their evolutionary origins. Current projects include discovering and analyzing genomic regions of extreme conservation in eukaryotic genomes and studying genome rearrangement in higher eukaryotes.
Cui H, Zhao N, Korkin D. "Multilayer View of Pathogenic SNVs in Human Interactome through In Silico Edgetic Profiling"; JMB (2018)
Johnson NT, Dhroso A, Hughes KJ, Korkin D, "Biological classification with RNA-seq data: Can alternatively spliced transcript expression enhance machine learning classifiers?", RNA (2018)
Liu S, Kandoth P, Warren S, Yeckel G, Heinz R, Alden J, Yang C, Jamai A, El-Mellouki T, Juvale P, Hill J, Baum T, Cianzio S, Whitham S, Korkin D, Meksem K, and Mitchum M. "A Soybean Cyst Nematode Resistance Gene Points to a New Mechanism of Plant Resistance to Pathogens"; Nature (2012)
Renecker J, Lyons E, Conant G, Pires C, Freeling M, Shyu CR, Korkin D. "Long Identical Multispecies Elements in Plant Genomes"; Proc Natl Acad Sci USA (2012)
January, 2020: Korkin Lab has released a structural genomics and interactomics map of SARS-COV-2 novel coronavirus available at http://korkinlab.org/wuhan The work's press release can be found HERE.
January, 2019: Korkin Lab is a part of a collaboration between WPI and Harvard's McLean Hospital to understand the mechanisms of depression for better diagnostics and treatment. Read more.
September, 2018: The Lab welcomes its new member: Huaming Sun, who joined us as a PhD Student co-advised with Shell Lab.
September, 2018: Dmitry received an NIH R21 grant.
August, 2018: Dmitry received a grant from AbbVie.
April, 2018: Suhas has won the best Poster Award in the Data Science, Cybersecurity, and Computer Science category for GRIE 2018. Congratulations, Suhas!