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The Boolean lab at UCSD focuses on developing computational approaches on complex biological datasets. The laboratory includes both dry-lab and wet-lab components for biological investigations, mathematical analysis, and computational model designs. Dr. Debashis Sahoo is the principal investigator who worked on identifying simple Boolean relationships between gene expression values and efficient analysis of Boolean functions in the field of formal verification of digital systems; hence the name 'Boolean Lab'. Dr. Sahoo and his team analyze large publicly available biological datasets to identify strong Boolean rules in a particular domain such as one tissue, one species or across species between mammals. The team focuses on special Boolean formulas known as Boolean invariants if all the data collected in a domain follow the rules. Dr. Sahoo and the team are dedicated to understanding the rules of life and human disease processes. To know more, please visit the 'Research' tab.
Discovery of broad impact:
Discovery of broad impact:
Dr. Sahoo identified the expression level of CDX2 as a predictive biomarker for favorable response to conventional chemotherapy among stage II colon cancer patients (Dalerba, Sahoo et al. NEJM 2016).
MiDReG tool successfully predicted B cell precursor genes (Sahoo et al. PNAS 2010) and identified a new precursor for B and T cells (Inlay, Bhattacharya, Sahoo et al. Genes Dev 2009)
The lab's Boolean approach have been used to simultaneously identify markers of stem and progenitor cells and prognostic biomarkers in human bladder cancer (Volkmer, Sahoo, Chin et al. PNAS 2012), colon cancer (Dalerba, Kalisky, Sahoo et al. Nat Biotech 2011; Dalerba, Sahoo et al. NEJM 2016), and prostate cancer (Sahoo et al. Oncotarget 2018)
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