Dr Srihari is a graph theorist by training. During his PhD at National University of Singapore (NUS), he ventured into Bioinformatics while trying to apply his graph algorithms and fixed-parameter tractable solutions to problems on protein-protein interaction (PPI) networks. He worked on the problem of identifying protein complexes from PPI networks, and developed a novel method (SPARC) that employs carefully selected functional interactions (using a ‘component-edge score’) to “densify” sparse regions of PPI networks and thereby identify sparse protein complexes. After graduating from NUS in 2012, he moved to The University of Queensland to continue work on biomolecular network models. While at UQ, he designed correlation and network-propagation based models to integrate and analyse multi-omics datasets in breast and pancreatic cancers. In particular, CONTOUR (Bioinformatics, 2013) employs a Bayesian approach to integrate PPI and gene co-expression, and identifies clusters (protein complexes) that have rewired – either changed their protein composition or gene co-expression – between conditions in cancer. Another approach, BOOLSPACE (IEEE/ACM Trans Comp Biol Bioinform, 2014) converts PPI and gene co-expression networks into a Boolean model with proteins representing Boolean variables and interactions representing Boolean clauses, and assesses rewiring as the minimum set of proteins that need to be “flipped” between conditions so as keep the networks SATISFIED. This model can be associated closely to the concept of “network controllability” put forward by Barabási and colleagues (Science, 2011). BOOLSPACE is also able to identify “moving targets” – genes that flip across stages of cancer progression – and is able to suggest ‘cover sets’ of target genes to attain maximum therapeutic efficacy (combination therapy). He also developed a method MutExSL (Biology Direct, 2015) to predict synthetic-lethal interactions based on identifying genes that are altered in a significantly mutually exclusive manner in cancers. This approach was selected for an American Association for Cancer Research (AACR) – Susan G. Komen award at the San Antonio Breast Cancer Symposium in San Antonio, Texas, USA (December 2015). Sriganesh also collaborates with experimental biologists and clinicians and has contributed (including one as joint-first author in Nucleic Acids Res, 2014) to publications in experimental and clinical biology. In 2016, Sriganesh took up an appointment as a Senior Research Scientist with the Lynn EMBL Australia group at South Australian Health and Medical Research Institute (SAHMRI), where he continues to investigate PPI networks and their rewiring using cancer cell-line data. Sriganesh is currently co-authoring a book (with Chern-Han and Professor Limsoon Wong, NUS) on algorithms for protein complex prediction which will be published by ACM Books (Morgan & Claypool, USA) in early-mid 2017. He is also a frequent reviewer for bioinformatics and computer science journals and conferences.
Srihari S, Kalimutho M, Lal S, Singla J, Patel D, Simpson PT, Khanna KK, Ragan MA (2016). Understanding the functional impact of copy number alterations in breast cancer using a network modelling approach, Molecular Biosystems (Royal Society of Chemistry), 12:963-972.
Srihari S, Singla J, Wong L, Ragan MA (2015). Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer, Biology Direct, 10:57 (Also presented at the San Antonio Breast Cancer Symposium, 2015).
Srihari S#, Yong CH, Patil A, Wong L (2015). Methods for protein complex prediction and their contributions towards understanding the organization, function and dynamics of complexes, FEBS Letters, 589 (19A):2590-2602 (Invited refereed paper to Special Issue on Intrinsically Disordered Proteins; Eds. Wilhelm Just & Vladimir Uversky).
Liu C*, Srihari S*, Lê Cao K-A, Chevenix-Trench G, Simpson PT, Ragan MA, Khanna KK (2014). A fine-scale dissection of the DNA double-strand break repair machinery and its implications for breast cancer therapy, Nucleic Acids Research, 42(10):6106-6127 (*Joint first-authors).
Srihari S, Raman V, Leong HW, Ragan MA (2014). Evolution and controllability of cancer networks: a Boolean perspective, IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1):83-94 (Also presented at the Cold Spring Harbor – Frontiers in Computational Biology conference, 2013).
Srihari S, Ragan MA (2013). Systematic tracking of dysregulated modules identifies novel genes in cancer, Bioinformatics 29(12): 1553--1561.
Srihari S, Ning K, Leong HW (2010). MCL-CAw: A refinement of MCL for detecting yeast complexes from weighted PPI networks by incorporating core-attachment structure, BMC Bioinformatics, 11:504.