Mukesh Bansal

Mukesh Bansal


Vice President, Psychogenics

Mukesh Bansal is an associate research scientist in the laboratory of Andrea Califano. He majored in physics at the Indian Institute of Technology and received his PhD in systems biology from University of Naples, Italy. His research interests include inferring transcriptional, posttranscriptional, posttranslational, and signaling networks from gene/miRNA expression and proteomics data, and dissecting these networks to identify master regulators (MR) of physiologic and pathologic phenotypes. He successfully applied this methodology to identify patient-specific MRs of lung cancer, helping to pave the path for personalized medicine. He also works on developing methods to predict drug mechanism of action, which he proved to be highly effective by predicting and validating novel targets of compounds. Recently he co-organized a community-based challenge to identify methods to predict compound synergy and confirmed that in silico assessment of compound synergy is indeed possible. He is also a co-inventor of a patent to predict indolent prostate cancer using a molecular signature. 

Education History

PhD, University of Naples, Italy
Human Genetics

Integrated MSc, Indian Institute of Technology, Kanpur, India


* Indicates these authors contributed equally to the paper.

Woo JH, Shimoni Y, Yang WS, Subramaniam P, Iyer A, Nicoletti P, Rodríguez Martínez M, López G, Mattioli M, Realubit R, Karan C, Stockwell BR, Bansal M*, Califano A*. Elucidating compound mechanism of action by network perturbation analysis. Cell. 2015 Jul 16;162(2):441-51. 

Nicoletti P, Bansal M, Lefebvre C, Guarnieri P, Shen Y, Pe'er I, Califano A, Floratos A. ABC transporters and the proteasome complex are implicated in susceptibility to Stevens-Johnson syndrome and toxic epidermal necrolysis across multiple drugs. PLoS One. 2015 Jun 25;10(6):e0131038.

Bansal M, Mendiratta G, Anand S, Kushwaha R, Kim R, Kustagi M, Iyer A, Chaganti RS, Califano A, Sumazin P. Direct ChIP-Seq significance analysis improves target prediction. BMC Genomics. 2015 May 26;16 Suppl 5:S4.

Davis H, Irshad S, Bansal M, Rafferty H, Boitsova T, Bardella C, Jaeger E, Lewis A, Freeman-Mills L, Giner FC, Rodenas-Cuadrado P, Mallappa S, Clark S, Thomas H, Jeffery R, Poulsom R, Rodriguez-Justo M, Novelli M, Chetty R, Silver A, Sansom OJ, Greten FR, Wang LM, East JE, Tomlinson I, Leedham SJ. Aberrant epithelial GREM1 expression initiates colonic tumorigenesis from cells outside the stem cell niche. Nat Med. 2015 Jan;21(1):62-70.

Bansal M, Yang J, Karan C, Menden MP, Costello JC, Tang H, Xiao G, Li Y,  Allen J, Zhong R, Chen B, Kim M, Wang T, Heiser LM, Realubit R, Mattioli M, Alvarez MJ, Shen Y; NCI-DREAM Community, Gallahan D, Singer D, Saez-Rodriguez J, Xie Y, Stolovitzky G, Califano A; NCI-DREAM Community. A community computational challenge to predict the activity of pairs of compounds. Nat Biotechnol. 2014 Dec;32(12):1213-22. 

Kushwaha R, Jagadish N, Kustagi M, Tomishima MJ, Mendiratta G, Bansal M, Kim HRSumazin P, Alvarez MJ, Lefebvre C, Villagrasa-Gonzalez P, Viale A, Korkola JE, Houldsworth J, Feldman DR, Bosl GJ, Califano A, Chaganti RS. Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency. Stem Cells. 2014 Oct 21.

Giorgi FM, Lopez G, Woo JH, Bisikirska B, Califano A, Bansal M. Inferring protein modulation from gene expression data using conditional mutual information. PLoS One. 2014 Oct 14;9(10):e109569.

Costello JC, Heiser LM, Georgii E, Gönen M, Menden MP, Wang NJ, Bansal M, Ammad-Ud-Din M, Hintsanen P, Khan SA, Mpindi JP, Kallioniemi O, Honkela A, Aittokallio T, Wennerberg K; NCI DREAM Community, Collins JJ, Gallahan D, Singer D, Saez-Rodriguez J, Kaski S, Gray JW, Stolovitzky G. A community effort to assess and improve drug sensitivity prediction algorithms. Nat Biotechnol. 2014 Jun 1.

Sonabend AM, Carminucci AS, Amendolara B, Bansal M, Leung R, Lei L, Realubit R, Li H, Karan C, Yun J, Showers C, Rothcock R, O J, Califano A, Canoll P, Bruce JN. Convection-enhanced delivery of etoposide is effective against murine proneural glioblastoma. Neuro Oncol. 2014 Mar 16.

Sonabend AM*, Bansal M*, Guarnieri P, Lei L, Amendolara B, Soderquist C, Leung R, Yun J, Kennedy B, Sisti J, Bruce S, Bruce R, Shakya R, Ludwig T, Rosenfeld S, Sims PA, Bruce JN, Califano A, Canoll P. The transcriptional regulatory network of proneural glioma determines the genetic alterations selected during tumor progression. Cancer Res. 2014 Mar 1;74(5):1440-51.

Chudnovsky Y, Kim D, Zheng S, Whyte WA, Bansal M, Bray MA, Gopal S, Theisen MA, Bilodeau S, Thiru P, Muffat J, Yilmaz OH, Mitalipova M, Woolard K, Lee J, Nishimura R, Sakata N, Fine HA, Carpenter AE, Silver SJ, Verhaak RG, Califano A, Young RA, Ligon KL, Mellinghoff IK, Root DE, Sabatini DM, Hahn WC, Chheda MG. ZFHX4 interacts with the NuRD core member CHD4 and regulates the glioblastoma tumor initiating cell state. Cell Rep. 2014 Jan 30;6(2):313-24.

Irshad S*, Bansal M*, Castillo-Martin M, Zheng T, Aytes A, Wenske S, Le Magnen C, Guarnieri P, Sumazin P, Benson MC, Shen MM, Califano A, Abate-Shen C. A molecular signature predictive of indolent prostate cancer. Sci Transl Med. 2013 Sep 11;5(202):202ra122.

Ying CY, Dominguez-Sola D, Fabi M, Lorenz IC, Hussein S, Bansal M, Califano A, Pasqualucci L, Basso K, Dalla-Favera R. MEF2B mutations lead to deregulated expression of the BCL6 oncogene in diffuse large B-cell lymphoma. Nat Immunol. 2013 Oct;14(10):1084-92.

Della Gatta G, Palomero T, Perez-Garcia A, Ambesi-Impiombato A, Bansal M, Carpenter ZW, De Keersmaecker K, Sole X, Xu L, Paietta E, Racevskis J, Wiernik PH, Rowe JM, Meijerink JP, Califano A, Ferrando AA. Reverse engineering of TLX oncogenic transcriptional networks identifies RUNX1 as tumor suppressor in T-ALL. Nat Med. 2012 Feb 26;18(3):436-40.

Sumazin P, Yang X, Chiu HS, Chung WJ, Iyer A, Llobet-Navas D, Rajbhandari P, Bansal M, Guarnieri P, Silva J, Califano A. An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma. Cell. 2011 Oct 14;147(2):370-81.

Bandaru P, Bansal M, Nemenman I. Mass conservation and inference of metabolic networks from high-throughput mass spectrometry data. J Comput Biol. 2011 Feb;18(2):147-54.

Cantone I, Marucci L, Iorio F, Ricci MA, Belcastro V, Bansal M, Santini S, di Bernardo M, di Bernardo D, Cosma MP. A yeast synthetic network for in vivo assessment of reverse-engineering and modeling approaches. Cell. 2009 Apr 3;137(1):172-81.

Della Gatta G*, Bansal M*, Ambesi-Impiombato A, Antonini D, Missero C, di Bernardo D. Direct targets of the Trp63 transcription factor revealed by a combination of gene expression profiling and reverse engineering. Genome Res. 2008 Jun;18(6):939-48.

Bansal M, di Bernardo D. Inference of gene networks from temporal gene expression profiles. IET Syst Biol. 2007 Sep;1(5):306-12. 

Cosentino C, Curatola W, Montefusco F, Bansal M, di Bernardo D, Amato F. Linear matrix inequalities approach to reconstruction of biological networks. IET Syst Biol. 2007 May;1(3):164-73. 

Cosentino C, Curatola W, Montefusco F, Bansal M, di Bernardo D, Amato F. Piecewise affine approach to inferring cell cycle regulatory network in fission yeast. Biomed Signal Proces. 2007 Jul;2(3)208-16.

Bansal M, Belcastro V, Ambesi-Impiombato A, di Bernardo D. How to infer gene networks from gene expression profiles. Mol Syst Biol. 2007;3:78.

Ambesi-Impiombato A, Bansal M, Liò P, di Bernardo D. Computational framework for the prediction of transcription factor binding sites by multiple data integration. BMC Neurosci. 2006 Oct 30;7 Suppl 1:S8. Review.

Bansal M, Della Gatta G, di Bernardo D. Inference of gene regulatory networks and compound mode of action from time course gene expression profiles. Bioinformatics. 2006 Apr 1;22(7):815-22.

Fantom Consortium: Carnici P, Kasukawa T, … Bansal M, et al. The transcriptional landscape of the mammalian genome. Science. 2005 Sep 2;309(5740):1559-63.

Book Chapters

Bansal M, Califano A. Genome-wide dissection of post-transcriptional and post-translational interactions. Methods Mol Biol. 2012;786:131-49.

Amato F, Bansal M, Cosentino C, Curatola W, di Bernardo D. Identification of regulatory pathways of the cell cycle fission yeast. Modelling and Control in Biomedical Systems; Elseview IFAC Publications. ISBN: 978-0-08-044530-4.

Ambesi A, Bansal M, Della Gatta G, di Bernardo D. Gene networks and application to drug discovery. DNA Microarrays: Current Applications; Horizon Bioscience publications. ISBN: 978-1-904933-25-0.

Mirzadeh N, Ricci F, Bansal M. Supporting user query relaxation in a recommender system. Lecture Notes in Computer Science 3182 Springer Publications 2004.


Diagnostic Markers of Indolent Prostate Cancer. PCT/US2013/055469.