The University of Texas at Dallas
Department of Mathematics, FO 35
800 West Campbell Road
Richardson, TX 75080-3021, USA
Office: FO 3.704K
B.Sc., Statistics, University of Delhi, India, 1994
M.Sc., Statistics, University of Delhi, India, 1996
Ph.D., Biostatistics, Ohio State University, Columbus, OH, 2003
Post doctoral, MD Anderson Cancer Center, Houston, TX, 2005
Peer-Reviewed Publications (Note: The underlined co-authors are my former/current students)
1. Biswas, S., Papachristou, C., Irwin, M. and Lin, S. (2003) “Linkage analysis of the simulated data Evaluations and comparisons of methods”, BMC Genetics, 4:S70.
2. Biswas, S. and Lin, S. (2004) “Evaluations of maximization procedures for estimating linkage parameters under heterogeneity”, Genetic Epidemiology, 26:206-217.
3. Lin, S. and Biswas, S. (2004) “On modeling locus heterogeneity using mixture distributions”, BMC Genetics, 5:29.
4. Biswas, S. and Berry, D.A. (2005) “Determining joint carrier probabilities of cancer causing genes using Markov chain Monte Carlo methods”, Genetic Epidemiology, 29:141-154.
5. Biswas, S., Lin, S., and Berry, D.A. (2005) “A new Bayesian approach incorporating covariate information for heterogeneity and its comparison with HLOD”, BMC Genetics, 6:S138.
6. Biswas, S. and Lin, S. (2006) “A Bayesian approach for incorporating variable rates of heterogeneity in linkage analysis”, Journal of the American Statistical Association, 101:1341-1351.
7. Huang, X., Biswas, S., Estey, E. H., and Berry, D.A. (2006) “Building and validating a prognostic index for biomarker studies”, Cancer Biomarkers, 2:97-101.
8. Huang, X., Biswas, S., Oki, Y., Issa, J-P., and Berry, D.A. (2007) “A parallel phase I/II clinical trial design for combination therapies”, Biometrics 63:429-436.
9. Biswas, S. and Lin, S. (2007) “Incorporating covariates in mapping heterogeneous traits A hierarchical model using empirical Bayes estimation”, Genetic Epidemiology, 31:684-696.
10. Biswas, S., Liu, D.D., Lee, J.J and Berry, D.A. (2009) “Bayesian Clinical Trials at the University of Texas MD Anderson Cancer Center”, Clinical Trials, 6:205-216.
11. Ahmad, N., Biswas, S., Bae, S., Meador, K., Huang, R., and Singh, K. (2009) “Association between obesity and asthma in US children and adolescents”, Journal of Asthma, 46:642-646.
12. Biswas, S. and Papachristou, C. (2010) “Accounting for Disease Model Uncertainty in Mapping Heterogeneous Traits A Bayesian Model Averaging Approach”, Human Heredity, 69:242-253.
13. Biswas, S. and Lin, S. (2012) “Logistic Bayesian LASSO for Identifying Association with Rare Haplotypes and Application to Age-Related Macular Degeneration”, Biometrics, 68:587-597.
14. Biswas, S., Tankhiwale, N., Blackford, A., Gutierrez Barrera, A.M., Ready, K., Lu, K., Amos, C.I., Parmigiani, G., Arun, B. (2012) “Assessing the Added Value of Breast Tumor Markers in Breast Cancer Genetic Risk Prediction Model BRCAPRO”, Breast Cancer Research and Treatment, 133:347-355.
15. Lingineni, R., Biswas, S., Ahmad, N., Jackson, B., Bae, S., Singh, K.P. (2012) “Risk Factors for Attention Deficit/Hyperactivity Disorder Among US Children: Results from a National Survey”, BMC Pediatrics, 12:50.
16. Shetty P.K., Thamake S.I., Biswas, S., Johansson S.L. and Vishwanatha J.K. (2012) “Reciprocal Regulation of Annexin A2 and EGFR with Her-2 in Her-2 Negative and Herceptin-Resistant Breast Cancer”, PLOS One, 7(9):e44299.
17. Biswas, S., Atienza, P., Chipman, J., Hughes, K., Gutierrez Barrera, A.M., Amos, C.I., Arun, B., Parmigiani, G. (2013) “Simplifying Clinical Use of the Genetic Risk Prediction Model BRCAPRO”, Breast Cancer Research and Treatment, 139: 571-579.
18. Biswas, S. and Papachristou, C. (2014) “Evaluation of Logistic Bayesian LASSO for Identifying Association with Rare Haplotypes”, BMC Proceedings, 8(Suppl 1): S54.
19. Satten, G.A., Biswas, S., Papachristou, C., Turkmen, A., and König, I.R. (2014) “Population-based association and gene by environment interactions in the Genetic Analysis Workshop 18”, Genetic Epidemiology, 38: S49-S56.
20. Biswas, S., Xia, S., and Lin, S. (2014) “Detecting Rare Haplotype-Environment Interaction with Logistic Bayesian LASSO”, Genetic Epidemiology, 38: 31-41.
21. Biswas, S., Arun, B., and Parmigiani, G. (2014) “Reclassification of Predictions for Uncovering Sub-Group Specific Improvement”, Statistics in Medicine, 33: 1914 - 1927.
22. Lykens, K., Moayad, N., Biswas, S., Reyes-Ortiz, C., Singh, K.P. (2014) “Impact of a community based implementation of REACH II Program for caregivers of Alzheimer’s patients”, PLOS One , 9(2): e89290.
23. Zhang, Y. and Biswas, S. (2015) “An Improved Version of Logistic Bayesian LASSO for Detecting Rare Haplotype-Environment Interactions With Application to Lung Cancer”, Cancer Informatics, 14(S2): 11-16.
24. Datta, A.S., Zhang, Y., Zhang, L., and Biswas, S. (2015) “Association of Rare Haplotypes on ULK4 and MAP4 Genes with Hypertension”, BMC Proceedings, in press
25. Mazzola, E., Blackford, A., Parmigiani, G., and Biswas, S. (2015) “Recent Enhancements to the genetic risk prediction model BRCAPRO”, Cancer Informatics, 14(S2): 147-157.
26. Datta, A.S. and Biswas, S. (2015) “Comparison of Haplotype-based Statistical Tests for Disease Association with Rare and Common Variants”, Briefings in Bioinformatics, doi: 10.1093/bib/bbv072.
27. Biswas, S., Atienza, P., Chipman, J., Blackford, A.L., Arun, B., Hughes, K., Parmigiani, G. (2016) “A Two-Stage Approach to Genetic Risk Assessment in Primary Care”, Breast Cancer Research and Treatment, 155: 375-383.
28. Zhang, Y., Lin, S., and Biswas, S. (2016) “Detecting rare and common haplotype-environment interaction under uncertainty of gene-environment independence assumption ”, Biometrics, in press.
1. Archer, K.J., Dobbin, K, Biswas, S., Day, R.S., Wheeler, D.C. and Wu, H. (2015) “Introductory Editorial: Computer Simulation, Bioinformatics, and Statistical Analysis of Cancer Data and Processes”, Cancer Informatics, Suppl. 2:247-251.
Grants and Contracts
1. Title: A Model for Individualized Risk Prediction of Contralateral Breast Cancer, Funding Agency: NCI/NIH, R21 CA186086-01, Role: PI, 09/01/2014 - 08/31/2017
2. Title: Efficacy Study of A Nicotine Barrier Cream, Funding Agency: CDC/UNT Health Science Center, R03-OH009815-01A1, Role: Co-I, 09/01/2014 - 08/31/2015 (PI: Y Liu)
3. Title: Genetic Risk Prediction in Primary Care, Funding Agency: NCI/NIH, R03 CA173834-01, Role: PI, 01/01/2013 - 12/31/2016
3. Title: Modeling Reclassification of Predictions, Funding Agency: Dana Farber Cancer Institute, Role: PI, 01/01/2014 - 06/30/2014
5. Title: Identifying rare haplotype-environment interactions using Logistic Bayesian Lasso, Funding Agency: NCI/NIH, R03 CA171011-01, Role: PI, 07/10/2012 - 06/30/2015
6. Title: Preliminary Evidence for a Two-Stage Approach for Adapting BRCAPRO to Primary Clinical Settings, Funding Agency: Dana Farber Cancer Institute, Role: PI, 10/01/2011 - 09/30/2012
7. Title: Evaluation of Tarrant County United Way Healthy Aging and Independent Living Initiative, Funding Agency: United Way of Tarrant County, Role: Co-I, Duration: 07/01/2010 - 06/30/2012 (PI: K Lykens).
8. Title: Improvement and Validation of BRCAPRO, Funding Agency: Susan G Komen for Cure, KG081303, Role: Co-I, Duration: 09/01/2009 - 07/31/2011 (PI: G Parmigiani).
9. Title: Validation of a Statistical Model for Prediction of Carrying Breast/Ovarian Cancer Susceptibility Genes BRCA1 and BRCA2, Funding agency: UNTHSC SPH Intramural Seed Grant, Role: PI, Duration: 10/06/2008 - 10/06/2009.
10. Title: Post-Baccalaureate Research Education Program and Retention Enhancement (PREPARE), Funding Agency: National Institute of General Medical Sciences, NIH, R25 GM078398-01, Role: Evaluation Coordinator, Duration: 09/30/2006 - 08/31/2010 (PI: JK Vishwanatha).
11. Title: Statistical methods for gene mapping - a new paradigm, Funding Agency: NHGRI/NIH, R01 5HG002657-03, Role: Consultant, Duration: 8/20/2005 - 12/31/2006 (PI: S. Lin)