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Your Environment. Your Health.

Project Publications: Boston University: Bioinformatics and Molecular Modeling Core

Superfund Research Program

Bioinformatics and Molecular Modeling Core

Project Leader: Stefano Monti
Co-Investigator: Sandor Vajda
Grant Number: P42ES007381
Funding Period: 2000-2021
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

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Visit the grantee's Twitter page View the grantee's Factsheet(377KB)



  • Kim S, Reed E, Monti S, Schlezinger JJ. 2021. A data-driven transcriptional taxonomy of adipogenic chemicals to identify white and brite adipogens. Environ Health Perspect 129(7):77006. doi:10.1289/EHP6886 PMID:34323617 PMCID:PMC8320370
  • Reed E, Monti S. 2021. Multi-resolution characterization of molecular taxonomies in bulk and single-cell transcriptomics data. Nucleic Acids Res 49(17):doi:10.1093/nar/gkab552 PMID:34226941 (ahead of print)


  • Chen L, Ouyang J, Wienand K, Bojarczuk K, Hao Y, Chapuy B, Neuberg D, Juszczynski P, Lawton LN, Rodig S, Monti S, Shipp M. 2019. 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 doi:10.3324/haematol.2019.216218 PMID:31471373 (in press)
  • Federico A, Karagiannis T, Karri K, Kishore D, Koga Y, Campbell J, Monti S. 2019. Pipeliner: a nextflow-based framework for the definition of sequencing data processing pipelines. Front Genet 10:614. doi:10.3389/fgene.2019.00614 PMID:31316552 PMCID:PMC6609566
  • Federico A, Monti S. 2019. hypeR: An R Package for Geneset Enrichment Workflows. Bioinformatics PMID:31498385 (in press)
  • Kartha V, Sebastiani P, Kern J, Zang L, Varelas X, Monti S. 2019. CaDrA: A computational framework for performing candidate driver analyses using genomic features. Front Genet 10:121. doi:10.3389/fgene.2019.00121 PMID:30838036 PMCID:PMC6390206
  • Li A, Chapuy B, Varelas X, Sebastiani P, Monti S. 2019. Identification of candidate cancer drivers by integrative epi-DNA and gene expression (iEDGE) data analysis. Sci Rep 9:16904. doi:10.1038/s41598-019-52886-z PMID:31729402 PMCID:PMC6858347
  • Li A, Lu X, Natoli T, Bittker J, Sipes N, Subramanian A, Auerbach SS, Sherr DH, Monti S. 2019. The Carcinogenome Project: in vitro gene expression profiling of chemical perturbations to predict long-term carcinogenicity. Environ Health Perspect 127:47002. doi:10.1289/EHP3986 PMID:30964323 PMCID:PMC6785232
  • Reed E, Moses E, Xiao X, Liu G, Campbell J, Perdomo C, Monti S. 2019. Assessment of a highly multiplexed RNA sequencing platform and comparison to existing high-throughput gene expression profiling techniques. Front Genet 10:150. doi:10.3389/fgene.2019.00150 PMID:30891063 PMCID:PMC6411637
  • Sebastiani P, Monti S, Morris M, Gurinovich A, Toshiko T, Andersen SL, Sweigart B, Ferrucci L, Jennings LL, Glass DJ, Perls TT. 2019. A Serum Protein Signature of APOE Genotypes in Centenarian. Aging-US doi:10.1111/acel.13023 PMID:31385390 PMCID:PMC6826130 (in press)




  • Stanford EA, Ramirez-Cardenas A, Wang Z, Novikov O, Alamoud K, Koutrakis P, Mizgerd JP, Genco CA, Kukuruzinska M, Monti S, Bais MV, Sherr DH. 2016. Role for the aryl hydrocarbon receptor and diverse ligands in oral squamous cell carcinoma migration and tumorigenesis. Mol Cancer Res 14(8):696-706. doi:10.1158/1541-7786.MCR-16-0069 PMID:27130942 PMCID:PMC4987205
  • Stanford EA, Wang Z, Mulas F, Landesman-Bollag E, Monti S, Smith BW, Seldin DC, Murphy GJ, Sherr DH. 2016. The role of the aryl hydrocarbon receptor in the development of cells with the molecular and functional characteristics of cancer stem-like cells. BMC Biol 14:20. doi:10.1186/s12915-016-0240-y PMID:26984638 PMCID:PMC4794823
  • Stanford EA, Wang Z, Novikov O, Ramirez-Cardenas A, Mulas F, Landesman-Bollag E, Monti S, Smith BW, Bais MV, Kukuruzinska M, Murphy GJ, Sherr DH. 2016. A role for the aryl hydrocarbon receptor (Ahr) in the production and function of breast and oral cancer stem-like cells and the potential therapeutic value of Ahr modulators. Toxicol Lett 259:S20. doi:10.1016/j.toxlet.2016.07.090



  • Gusenleitner D, Auerbach SS, Melia T, Gomez HF, Sherr DH, Monti S. 2014. Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS One 9(7):e102579. doi:10.1371/journal.pone.0102579 PMID:25058030 PMCID:PMC4109923
  • Parks A, Pollastri MP, Hahn ME, Stanford EA, Novikov O, Franks DG, Haigh SE, Narasimhan S, Ashton TD, Hopper TG, Kozakov D, Beglov D, Vajda S, Schlezinger JJ, Sherr DH. 2014. In silico identification of an aryl hydrocarbon receptor antagonist with biological activity in vitro and in vivo. Mol Pharmacol 86(5):593-608. doi:10.1124/mol.114.093369 PMID:25159092 PMCID:PMC4201140
  • Pillai HK, Fang M, Beglov D, Kozakov D, Vajda S, Stapleton HM, Webster TF, Schlezinger JJ. 2014. Ligand binding and activation of PPARγ by Firemaster® 550: effects on adipogenesis and osteogenesis in vitro. Environ Health Perspect 122(11):1225-1232. doi:10.1289/ehp.1408111 PMID:25062436 PMCID:PMC4216168


  • Leung A, Nah SK, Reid W, Ebata A, Koch CM, Monti S, Genereux JC, Wiseman RL, Wolozin B, Connors LH, Berk JL, Seldin DC, Mostoslavsky G, Kotton DN, Murphy GJ. 2013. Induced pluripotent stem cell modeling of multisystemic, hereditary transthyretin amyloidosis. Stem Cell Reports 1(5):451–463. doi:10.1016/j.stemcr.2013.10.003 PMID:24286032 PMCID:PMC3841264
  • Sherr DH, Monti S. 2013. The role of the aryl hydrocarbon receptor in normal and malignant B cell development. Semin Immunopathol 35(6):705-716. doi:10.1007/s00281-013-0390-8 PMID:23942720 PMCID:PMC3824572
  • Smith BW, Rozelle SS, Leung A, Ubellacker J, Parks A, Nah SK, French D, Gadue P, Monti S, Chui DK, Steinberg MH, Frelinger AL, Michelson AD, Theberge R, McComb ME, Costello CE, Kotton DN, Mostoslavsky G, Sherr DH, Murphy GJ. 2013. The aryl hydrocarbon receptor directs hematopoietic progenitor cell expansion and differentiation. Blood 122:376-385. doi:10.1182/blood-2012-11-466722 PMID:23723449 PMCID:PMC3716202


  • Beglov D, Brenke R, Chuang G, Hall D, Landon MR, Ngan CM, Shen Y, Thiel S, Zerbe B, Kozakov D, Vajda S. 2009. Identification of druggable hot spots on proteins and in protein-protein interfaces. In: Computational Protein-Protein Interactions.
  • Brenke R, Kozakov D, Chuang G, Beglov D, Hall D, Landon MR, Mattos C, Vajda S. 2009. Fragment-based identification of druggable 'hot spots' of proteins using Fourier domain correlation techniques. Bioinformatics 25(5):621-627. doi:10.1093/bioinformatics/btp036 PMID:19176554 PMCID:PMC2647826


  • Prasad JC, Goldstone JV, Camacho CJ, Vajda S, Stegeman JJ. 2007. Ensemble modeling of substrate binding to cytochromes P450: Analysis of catalytic differences between CYP1A orthologues. Biochemistry 46(10):2640-2654. PMID:17300179
  • Silberstein M, Damborsky J, Vajda S. 2007. Exploring the binding sites of the haloalkane dehalogenase DhlA from Xanthobacter autotrophicus GJ10. Biochemistry 46(32):9239-9249. doi:10.1021/bi700336y PMID:17645312
  • Vajda S. 2007. Mapping of Proteins for the Binding of Functional Groups from Xenobiotics. (non-peer reviewed)


  • Clodfelter KH, Holloway MG, Hodor P, Park S, Ray WJ, Waxman DJ. 2006. Sex-dependent liver gene expression is extensive and largely dependent upon signal transducer and activator of transcription 5b (STAT5b): STAT5b-dependent activation of male genes and repression of female genes revealed by microarray analysis. Mol Endocrinol 20(6):1333-1351. doi:10.1210/me.2005-0489 PMID:16469768
  • Clodfelter KH, Waxman DJ, Vajda S. 2006. Computational solvent mapping reveals the importance of local conformational changes for broad substrate specificity in mammalian cytochromes P450. Biochemistry 45(31):9393-407. PMID:16878974
  • Kaya T, Mohr SC, Waxman DJ, Vajda S. 2006. Computational screening of phthalate monoesters for binding to PPARgamma. Chem Res Toxicol 19(8):999-1009. doi:10.1021/tx050301s PMID:16918238
  • Landon MR, Lancia DR, Clodfelter KH, Vajda S. 2006. Clustering of domains of functionally related enzymes in the interaction database PRECISE by the generation of primary sequence patterns. Journal of Molecular Graphics and Modelling 24(6):426-433. PMID:16221553


  • Scammell MK. 2005. Roots of community research: primer on the legacy of participatory research partnerships. Race, Poverty & The Environment XINo.2:
  • Sheu S, Kaya T, Waxman DJ, Vajda S. 2005. Exploring the binding site structure of the PPAR gamma ligand-binding domain by computational solvent mapping. Biochemistry 44(4):1193-1209. doi:10.1021/bi048032c PMID:15667213
  • Sheu S, Lancia DR, Clodfelter KH, Landon MR, Vajda S. 2005. PRECISE: a database of predicted and consensus interaction sites in enzymes. Nucleic Acids Res 33(Databaseissue):D206-D211. doi:10.1093/nar/gki091 PMID:15608178 PMCID:PMC540045


  • Ahluwalia A, Clodfelter KH, Waxman DJ. 2004. Sexual dimorphism of rat liver gene expression: Regulatory role of growth hormone revealed by deoxyribonucleic acid microarray analysis. Mol Endocrinol 18(3):747-760. PMID:14684848
  • Comeau SR, Gatchell DW, Vajda S, Camacho CJ. 2004. ClusPro: A fully automated algorithm for protein-protein docking. Nucleic Acids Res 32:W96-W99. PMID:15215358
  • Comeau SR, Gatchell DW, Vajda S, Camacho CJ. 2004. ClusPro: An automated docking and discrimination method for the prediction of protein complexes. Bioinformatics 20(1):45-50. PMID:14693807
  • Prasad JC, Vajda S, Camacho CJ. 2004. Consensus alignment server for reliable comparative modeling with distant templates. Nucleic Acids Res 32:W50-W54. PMID:15215349


  • Kortvelyesi T, Dennis S, Silberstein S, Brown L, Vajda S. 2003. Algorithms for computational solvent mapping of proteins. Proteins: Structure, Function, and Genetics 51(3):340-351. PMID:12696046
  • Kortvelyesi T, Silberstein M, Dennis S, Vajda S. 2003. Improved mapping of protein binding sites. J Comput Aided Mol Des 17(2-4):173-186. PMID:13677484
  • Prasad JC, Comeau SR, Vajda S, Camacho CJ. 2003. Consensus alignment for reliable framework prediction in homology modeling. Bioinformatics 19(13):1682-1691. PMID:12967965
  • Prasad JC, Silberstein M, Camacho CJ, Vajda S. 2003. Homology modeling of proteins using multiple models and consensus sequence alignment. Lecture Notes in Bioinformatics 2812:389-401.
  • Silberstein M, Dennis S, Brown L, Kortvelyesi T, Clodfelter KH, Vajda S. 2003. Identification of substrate binding sites in enzymes by computational solvent mapping. J Mol Biol 332(5):1095-1113. doi:10.1016/j.jmb.2003.08.019 PMID:14499612


  • Dennis S, Kortvelyesi T, Vajda S. 2002. Computational mapping identifies the binding sites of organic solvents on proteins. Proc Natl Acad Sci U S A 99(7):4290-4295. PMID:11904374
  • Dennis S, Kortvelyesi T, Vajda S. 2002. Computational solvent mapping for the analysis of enzyme active sites. Abstr Pap Am Chem Soc 224:221-COMPPart1.
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