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Causal modeling of CALGB 80405 (Alliance) identifies network drivers of metastatic colorectal cancer (mCRC).  Das RK, Furchtgott L, Cunha D, Fang-Shu O, Innocenti F, Heinz-Josef Lenz, Meyerhardt J, Rich K, Latourelle J, Niedzwiecki D, Nixon A, O’Reilly EM, Wuest D, Hayete B, Khalil I, Venook A. ASCO Annual Meeting. Chicago, Illinois. 2018.

Machine learning approach to personalized medicine in breast cancer patients: development of data-driven, personalized, causal modeling through identification and understanding of optimal treatments for predicting better disease outcomes. Kaplan GH, Berry AB, Rinn KJ, Ellis ED, Birchfield GR, Wahl TA, Liu X, Tameishi M, Beatty JD, Dawson PL, Mehta VK, Holman A, Atwood MK, Alexander S, Bonham C, Summers L, Khalil I, Hayete B, Wuest D, Zheng W, Liu Y, Wang X, Brown TD. AACR Annual Meeting. Chicago, Illinois. 2018.

Accurate Prediction of Clinical Disease Progression in Patients With Advanced Fibrosis Due to NASH using a Bayesian Machine Learning Approach. Latourelle J, Tu J, Das R, Furchtgott L, Schoeberl B, Smiechowski B, Church B, Khalil I, Hayete B, Djedjos S, Nguyen T, Xiao Y, Aguilar R, Chen G, Subramnian, Myers R, Ratziu V, Nezam A, Bosch, Goodman Z, Harrison S, Sanyal A. The International Liver Congress™. Paris, France. 2018.

Reconstruction and simulation of regulatory networks in the Htt allelic series using causal machine learning. Latourelle J, Yan R, Beste M, Yang T, Hayete B, Khalil I, Aaronson J, Rosinski J. 13th Annual HD Therapeutics Conference. Palm Springs, CA. 2018.

Systems biology and in vitro validation identifies family with sequence similarity 129 member A (FAM129A) as an asthma steroid response modulator. McGeachie MJ, Clemmer GL, Hayete B, Xing H, Runge K, Wu AC, Jiang X, Lu Q, Church B, Khalil I, Tantisira K, Weiss S. The Journal of allergy and clinical immunology. February 27, 2018. DOI: 10.1016/j.jaci.2017.11.059



Multiple Myeloma Drivers of High Risk and Response to Stem Cell Transplantation Identified by Causal Machine Learning: Out-of-Cohort and Experimental Validation. Furchtgott L, Bolomsky A, Gruber F, Samur M, Keats J, Yeesil J, Stangelberge K, Attal M, Moreau P, Avet-Loiseau H, Runge K, Wuest D, Rich K, Khalil I, Hayete B, Ludwig H, Munshi N, Auclair D. ASH Annual Meeting 2017. 3029.

Large-scale identification of clinical and genetic predictors of motor progression in patients with newly diagnosed Parkinson’s disease: a longitudinal cohort study and validation. Latourelle J, Beste M, Hadzi T, Miller R, Oppenheim J, Valko M, Wuest D, Church B, Khalil I, Hayete, B, Venuto C. Lancet Neurology Online. September 25, 2017. DOI http://dx.doi.org/10.1016/S1474-4422(17)30331-9

A Bayesian mathematical model of motor and cognitive outcomes in Parkinson’s disease. Hayete B, Wuest D, Laramie J, McDonagh P, Church B, Eberly S, et al. (2017) PLoS ONE 12(6): e0178982. https://doi.org/10.1371/journal.pone.0178982

Statistical Modeling of CALGB 80405 (Alliance) to Identify Influential Factors in Metastatic Colorectal Cancer (CRC) Dependent on Primary (1o) Tumor Side. Furchtogott L, Swanson D, Hayete B, Khalil, I, Wuest D, Rich K, Nixon AB, Niedzwiecki D, Meyerhardt JA, O’Reilly EM, Ou F, Heinz Josef L, Innocenti F, Venook AP. ASCO Annual Meeting 2017. 3528.

Predictors of Disease Modifying Therapy Initiation in Patients with Multiple Sclerosis Using Electronic Health Records Data-A Machine Learning Perspective. Icten Z, Hitchcock C, Davis S, Ciofani D, Sanky M, Hadzi T, Khalil I, Alas V. ISPOR Annual Meeting 2017.

Prediction of Hypoglycemia Risk Among Patients with Type 2 Diabetes (T2D) Using an Ensemble-Based, Hypothesis-Free Procedure. Thai N, Wei LJ, Alas V, Khalil I, Berhanu P, Dalal MR, Sung J. ISPOR Annual Meeting 2017.

Machine Learning Methodology Predicts Comorbidities are Associated With Increased Total Healthcare Costs Among Patients With Severe Peripheral Artery Disease. Berger JS, Haskell L, Ting W, Lurie F, Eapen Z, Valko M, Alas V, Rich K, Crivera C, Schein J. Quality of Care and Outcomes Research in Cardiovascular Disease and Stroke 2017 Scientific Sessions.

Novel Predictive Modeling Identifies and Quantifies Factors That Predict the Risk of Hypoglycemia in Patients with Type 2 Diabetes (T2D). Thai N, Wei L, Anderson J, Alas V, Zhou S, Berhanu P, Sung J, Dalal M. AMCP Managed Care Specialty Pharmacy Annual Meeting 2017.

Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells. Gendelman R, Xing H, Mirzoeva OK, Sarde P, Curtis C, Feiler H, McDonagh P, Gray JW, Khalil I, Korn WM. Cancer Research. Cancer Res January 13 2017 DOI: 10.1158/0008-5472.CAN-16-0512.


Bayesian Network Models of Multiple Myeloma: Drivers of High Risk and Durable Response. Gruber F, Hayete B, Keats J, McBride K, Runge K, DeRome M, Lonial S, Khalil I, Auclair D, ASH Annual Meeting. 2016.

Inferring Gene Networks for Strains of Dehalococcoides Highlights Conserved Relationships between Genes Encoding Core Catabolic and Cell-Wall Structural Proteins. Mansfeldt CB, Heavner GW, Rowe AR, Hayete B, Church BW, Richardson RE (2016) PLoS ONE 11(11): e0166234. doi:10.1371/journal.pone.0166234.

Machine Learning Methodology Identifies Predictors of a Cardiovascular Composite Measure Among Severe Peripheral Artery Disease Patients. Ting W, Haskell L, Lurie F, Berger JS, Eapen Z, Valko M, Alas V, Rich K, Crivera C, Schein J, AHA Scientific Sessions 2016. 14448

Using Clinical Trial and Real World Data to Bridge Efficacy to Effectiveness of Fingolimod in Multiple Sclerosis Patients. Ivanov V, Torgovitsky R, Tchetgen E, Church B, Alas V, Khalil I, Risson V, Kahler K, Olson M, ISPOR. 2016. PND8.

The Health Care Cost of Primary Headache and Associated Co-Morbidities. Valko M, Alas V, Strickland I, Staats P, Errico J, AMCP. 2016. G27

Novel Predictive Modeling Identifies and Quantifies Factors That Predict the Risk of Hypoglycemia in Patients with Type 2 Diabetes (T2D). Thai N, Wei L, Anderson J, Alas V, Zhou S, Berhanu P, Sung J, Dalal M, AMCP. 2016. E26.

Identification of Clinical and Genetic Predictors of Parkinson’s Disease Progression via Bayesian Machine Learning. Latourelle J, Beste M, Hadzi T, Hayete B, Miller R, Oppenheim J, Valko M, Wuest D, Khalil I, Venuto C, World Parkinson’s Congress (WPC), 2016. 1312.

Data-Driven Reconstruction and Simulation of Transcriptional Regulatory Networks in the Htt Allelic Series. Michael Beste, Tun-Hsiang Yang, Jeanne Latourelle, Boris Hayete , Liliana Menalled , Dani Brunner , Vadim Alexandrov , Seung Kwak, David Howland, Jeff Aaronson , Iya Khalil, James Rosinski. CHDI Foundation, Inc.‘s 11th Annual HD Therapeutics Conference. Palm Springs, CA. 2016.

Reverse Engineering and Evaluation of Prediction Models for Progression to Type 2 Diabetes: An Application of Machine Learning Using Electronic Health Records. Anderson JP, Parikh JR, Shenfeld DK, Ivanov V, Marks C, Church BW, Laramie JM, Mardekian J, Piper BA, Willke RJ, Rublee DA.  Journal of Diabetes Science and Technology. 2016. 10(1):6-18. PMID: 26685993


Clinical and Economic Burden of Commercially Insured Patients with Acromegaly in the United States: A Retrospective Analysis. Hilary Placzek, PhD, MPH; Yaping Xu, MD, MPH; Yunming Mu, PhD; Susan M. Begelman, MD; and Maxine Fisher, PhD, J Managed Care Spec Pharm. 2015;21(12):1106-14

Investigation of Mechanisms of Response in Multiple Myeloma Via Bayesian Causal Inference: An Early Analysis of the CoMMpass Study Data. Fred Gruber, Boris Hayete, Jonathan Keats, Kyle McBride, Karl Runge, Mary DeRome, Sagar Lonial, Iya Khalil, Daniel Auclair. American Society of Hematology (ASH) 57th Annual Meeting & Exposition. Orlando, FL. 2015.

Treatment Patterns Among Schizophrenia Patients Receiving Paliperidone Palmitate or Atypical Oral Antipsychotics in Community Behavioral Health Organizations. Jeffrey P. Anderson, Kruti Joshi, Zeynep Icten, Veronica Alas. 28th Annual US Psychiatric and Mental Health Congress. San Diego, CA. 2015.

Predictors of Remission in Schizophrenia Patients Treated With Paliperidone Palmitate or Oral Antipsychotics in Community Behavioral Health Organizations. Zeynep Icten, Kruti Joshi, Jeff Anderson, Veronica Alas. 28th Annual US Psychiatric and Mental Health Congress. San Diego, CA. 2015.

Power of Reverse Engineering and Forward Simulation Platform for Driving Precision Medicine. Khalil I, Wasserman S. Pharmaceutical R&D Information Systems Management Executive Forum. Plainsboro Township, NJ. 2015.


Novel Predictive Models for Metabolic Syndrome Risk- A “Big Data” Analytic Approach. Steinberg GB, Church BW, McCall CJ, Scott AB, Kalis BP. Am J Manag Care. 2014. 20(6):e221-e228. PMID: 25180505

Identification of Determinants of Progression to Type 2 Diabetes Using Electronic Health Records and Big Data Analytics. Anderson JP, Parikh JR, Shenfeld DK, Church BW, Laramie JM, Piper BA, Willke RJ, Mardekian J, Rublee DA. ISPOR 19th International Meeting. Montreal, Canada. 2014. PDB27.


HD causal modeling using network ensemble simulations of gene expression data. Jong-Min Lee, Kevin Correia, Douglas D. Barker, James F. Gusella,  Marcy E. MacDonald, Paul D. McDonagh, Jignesh R. Parikh, Iya G. Khalil, Keith Elliston, Seung Kwak. CHDI Foundation, Inc.‘s Annual HD Therapeutics Conference. Palm Springs, CA.

A mathematical model of long-term outcomes in Parkinson’s disease. Hayete B, Laramie J, Bienkowska J, Eberly S, Khalil I, Lang A, Marek K, Oakes D, Shoulson I, Singleton A, Song T, Verma A, Wien M, Ravina B. 17th International Congress of Parkinson’s Disease and Movement Disorders. Sydney, Australia. 2013. LBA-19.

Data-driven computational modeling to identify biomarkers of response to lenvatinib (E7080) in melanoma.Kadowaki T, Funahashi Y, Matsui J, Pavan K, Sachdev P, O’Brien J, Xing H, McDonagh PD, Khalil I, Kurzrock R, Hong DS, Nemunaitis J. 104th Annual Meeting of the American Association for Cancer Research. Washington, DC. 2013. 4025.


Learning Models for Metabolic Syndrome from Medical Claims Data. Church B, Steinberg G. Strata Rx Conference. San Francisco, CA. 2012.

Confirmation of peroxiredoxin II as a driver gene for doxorubicin sensitivity identified from drug-induced expression profiling of the NCI-60 cell lines using Reverse Engineering (REFS) network models. Monks A, Hose CD, Hayete B, Runge K, DeCaprio D, Teicher BA, Khalil I, McDonagh PD, Doroshow JH. 103rd Annual Meeting of the American Association for Cancer Research. Chicago, IL. 2012. 5663.

Reverse-engineered, forward-simulation of MEK-dependent molecular networks reveal novel regulators of cell cycle and cancer cell survival. Gendelman R, Xing H, Sarde P, Mirzoeva OK, Feiler H, Gray JW, McDonagh PD, Khalil I, Korn WM. 103rd Annual Meeting of the American Association for Cancer Research. Chicago, IL. 2012. 986.


Causal modeling using network ensemble simulations of genetic and gene expression data predicts genes involved in rheumatoid arthritis. Xing H, McDonagh PD, Bienkowska J, Cashorali T, Runge K, Miller RE, Decaprio D, Church B, Roubenoff R, Khalil IG, Carulli J. PLoS Comput Biol. 2011. 7(3):e1001105. PMID: 21423713


Quantification and analysis of combination drug synergy in high-throughput transcriptome studies. Gümüs ZH, Siso-Nadal F, Gjrezi A, McDonagh P, Khalil I, Giannakakou P, Weinstein H. IEEE International Conference on Bioinformatics and Bioengineering, 2010. pp. 238-243.

The potential of biologic network models in understanding the etiopathogenesis of ovarian cancer. Khalil I, Brewer MA, Neyarapally T, Runowicz CD. Gynecol Oncol. 2010. 116(2):282-5. PMID: 19931138


Cross-talk between signaling pathways can generate robust oscillations in calcium and cAMP. Siso-Nadal F, Fox JJ, Laporte SA, Hébert TE, Swain PS. PLoS One. 2009. 4(10):e7189. PMID: 19844582

Customized care 2020: how medical sequencing and network biology will enable personalized medicine.Boguski MS, Arnaout R, Hill C. F1000 Biol Rep. 2009. 1:73. PMID: 20948615


Achieving confidence in mechanism for drug discovery and development. Pitluk Z, Khalil I. Drug Discov Today. 2007. 12(21-22):924-30. PMID: 17993410

A systems biology dynamical model of mammalian G1 cell cycle progression. Haberichter T, Mädge B, Christopher RA, Yoshioka N, Dhiman A, Miller R, Gendelman R, Aksenov SV, Khalil IG, Dowdy SF. Mol Syst Biol. 2007. 3:84. PMID: 17299420


An integrated approach for inference and mechanistic modeling for advancing drug development. Aksenov SV, Church B, Dhiman A, Georgieva A, Sarangapani R, Helmlinger G, Khalil IG. FEBS Lett. 2005. 579(8):1878-83. PMID: 15763567

Systems biology for cancer. Khalil IG, Hill C. Curr Opin Oncol. 2005. 17(1):44-8. PMID: 15608512


The statistical mechanics of complex signaling networks: nerve growth factor signaling. Brown KS, Hill CC, Calero GA, Myers CR, Lee KH, Sethna JP, Cerione RA. Phys Biol. 2004. 1(3-4):184-95. PMID: 16204838

Data-driven computer simulation of human cancer cell. Christopher R, Dhiman A, Fox J, Gendelman R, Haberitcher T, Kagle D, Spizz G, Khalil IG, Hill C. Ann N Y Acad Sci. 2004. 1020:132-53. PMID: 15208190

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