Stefano Monti, PhD

Associate Professor, Medicine

Stefano Monti
75 E. Newton St Evans Building


Stefano Monti is a Computational Biologist and joined the BU faculty as an associate professor in January 2011 in the section of Computational Biomedicine, with a joint appointment in the Bioinformatics program. Monti received his Ph.D. in Intelligent Systems and Artificial Intelligence from the University of Pittsburgh, and completed his training with a post-doctoral fellowship at the Robotics Institute at Carnegie Mellon. His doctoral and post-doctoral research focused on the development of machine learning and knowledge discovery methodologies, with a particular emphasis on probabilistic reasoning and Bayesian approaches to modeling biomedical data. Since 2001, he has worked in the field of Cancer Genomics, first as a Research Scientist at the Whitehead Institute’s Center for Genome Research, and later as a Computational Biologist in the Cancer Program at the Broad Institute, of which he remains an affiliate member.

Other Positions

  • Associate Professor, Biostatistics, Boston University School of Public Health
  • Member, Bioinformatics Graduate Program, Boston University
  • Member, BU-BMC Cancer Center, Boston University
  • Member, Evans Center for Interdisciplinary Biomedical Research, Boston University
  • Graduate Faculty (Primary Mentor of Grad Students), Boston University School of Medicine, Graduate Medical Sciences
  • Member, Genome Science Institute, Boston University


  • University of Pittsburgh, PhD
  • University of Pittsburgh, MS
  • University of Houston, MS
  • Università degli Studi di Udine, BS

Classes Taught

  • GMSMM730


  • Published on 3/23/2020

    Chandler KB, Alamoud KA, Stahl VL, Nguyen BC, Kartha VK, Bais MV, Nomoto K, Owa T, Monti S, Kukuruzinska MA, Costello CE. ß-Catenin/CBP inhibition alters epidermal growth factor receptor fucosylation status in oral squamous cell carcinoma. Mol Omics. 2020 Mar 23. PMID: 32203567.

    Read at: PubMed
  • Published on 2/15/2020

    Federico A, Monti S. hypeR: an R package for geneset enrichment workflows. Bioinformatics. 2020 Feb 15; 36(4):1307-1308. PMID: 31498385.

    Read at: PubMed
  • Published on 1/13/2020

    Stampouloglou E, Cheng N, Federico A, Slaby E, Monti S, Szeto GL, Varelas X. Yap suppresses T-cell function and infiltration in the tumor microenvironment. PLoS Biol. 2020 01; 18(1):e3000591. PMID: 31929526.

    Read at: PubMed
  • Published on 11/15/2019

    Li A, Chapuy B, Varelas X, Sebastiani P, Monti S. Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis. Sci Rep. 2019 11 15; 9(1):16904. PMID: 31729402.

    Read at: PubMed
  • Published on 9/1/2019

    Gurinovich A, Bae H, Farrell JJ, Andersen SL, Monti S, Puca A, Atzmon G, Barzilai N, Perls TT, Sebastiani P. PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects. Bioinformatics. 2019 Sep 01; 35(17):3046-3054. PMID: 30624692.

    Read at: PubMed
  • Published on 8/30/2019

    Chen L, Ouyang J, Wienand K, Bojarczuk K, Hao Y, Chapuy B, Neuberg D, Juszczynski P, Lawton LN, Rodig SJ, Monti S, Shipp MA. CXCR4 upregulation is an indicator of sensitivity to B-cell receptor/PI3K blockade and a potential resistance mechanism in B-cell receptor-dependent diffuse large B-cell lymphomas. Haematologica. 2020 May; 105(5):1361-1368. PMID: 31471373.

    Read at: PubMed
  • Published on 8/5/2019

    Sebastiani P, Monti S, Morris M, Gurinovich A, Toshiko T, Andersen SL, Sweigart B, Ferrucci L, Jennings LL, Glass DJ, Perls TT. A serum protein signature of APOE genotypes in centenarians. Aging Cell. 2019 12; 18(6):e13023. PMID: 31385390.

    Read at: PubMed
  • Published on 6/28/2019

    Federico A, Karagiannis T, Karri K, Kishore D, Koga Y, Campbell JD, Monti S. Pipeliner: A Nextflow-Based Framework for the Definition of Sequencing Data Processing Pipelines. Front Genet. 2019; 10:614. PMID: 31316552.

    Read at: PubMed
  • Published on 4/1/2019

    Li A, Lu X, Natoli T, Bittker J, Sipes NS, Subramanian A, Auerbach S, Sherr DH, Monti S. The Carcinogenome Project: In Vitro Gene Expression Profiling of Chemical Perturbations to Predict Long-Term Carcinogenicity. Environ Health Perspect. 2019 04; 127(4):47002. PMID: 30964323.

    Read at: PubMed
  • Published on 3/5/2019

    Reed E, Moses E, Xiao X, Liu G, Campbell J, Perdomo C, Monti S. Assessment of a Highly Multiplexed RNA Sequencing Platform and Comparison to Existing High-Throughput Gene Expression Profiling Techniques. Front Genet. 2019; 10:150. PMID: 30891063.

    Read at: PubMed

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