SELECTED MANUSCRIPTS

Coming Before long

  • Shamshoian J., Senturk D., Jeste S., Telesca D., Bayesian Covariance Regression in Functional Data.

  • Watson G.L., Reid C., Jerrett One thousand , and Telesca D., Prediction and Model Evaluation for Space-Time Data. [arxiv]

  • Shamshoian J., Senturk D., Jeste South., Telesca D., Bayesian Analysis of Region Referenced Functional Information.

  • Watson G.50., Reid C., Jerrett Chiliad , and Telesca D., Treeging.

Functional Data Analysis

  • Shamshoian J., Senturk D., Jeste Southward., Telesca D. (2020) Bayesian Analysis of Longitudinal and Multidimensional Functional Data. Biostatistics (In Printing)[arxiv]

  • Telesca D. (2015). Bayesian Analysis of Curves Shape Variation through Registration and Regression. In Nonparametric Bayesian Methods in Biostatistics. Eds. Mitra R. and Mueller P. Springer.

  • Erosheva Eastward., Matzueda R., Telesca, D. (2014). Breaking Bad: Reviewing Two Decades of Life Course Data Analysis in Criminology and Beyond. Almanac Reviews of Statistics and Its Applications, 1, 301–332.

  • Telesca D., Inoue 50.Y.T., Neira M., Gleave M., Nelson C and Etzioni R. (2009). Differential Expression and Network Inferences through Functional Data Modeling. Biometrics, 65, 793–804.

  • Telesca D., Erosheva E., Kreger D. and Matzueda R. (2012). Modeling Criminal Careers equally Departures from a Unimodal Population Age-Crime Curve: The Example of Marijuana Utilize. JASA, 107, 1427–1440.

  • Telesca D. and Inoue L.Y.T. (2008). Bayesian Hierarchical Curve Registration. JASA, 103 (481), 328–339.

Functional Encephalon Imaging

  • Li Q.,  Senturk D., Saccharide C., DiStefano C., Jeste Southward., Shamshoian J. Telesca D. (2020) Region-referenced Spectral Power Dynamics of EEG Signals: a Hierarchical Modeling Approach. The Register of Practical Statistics (In Press) [arxiv]

  • Scheffler A., Telesca D., Li Q.,  Sugar C., DiStefano C., Jeste Due south., Senturk D. (2020) Hybrid Principal Components Assay For Region-Referenced Longitudinal Functional EEG Data. Biostatistics, 21(i), pp. 139-157.

  • Li Q., Senturk D., Sugar C. A., Jeste. Due south., DiStefano C., Frohlich J., Telesca D.  (2019) Inferring Brain Signals Synchronicity from a Sample of EEG Readings. JASA, 114 (527), pp. 991-1001. [arxiv]

  • Scheffler A.W., Telesca D., Saccharide C.A., Jeste S., Dickinson A., DiStefano C., Senturk D. (2019). Covariate adapted region-referenced generalized functional linear model for EEG data. Statistics in Medicine, 38 (xxx), pp. 5587-5602.

  • Hasenstab 1000., Scheffler A., Telesca D., Saccharide C.A.. Jeste S., DiStefano C., and Senturk D. (2017) A Multi-Dimensional Functional Main Components Analysis of EEG Data. Biometrics, Vol. 73(3), pp. 999-1009.

  • Senturk D., Hasenstab Thousand., Carbohydrate C., Telesca D., Jeste S. (2016) Robust functional clustering of ERP data with application to a written report of implicit learning in autism. Biostatistics, Vol. 17 (iii), pp. 484-498.

  • Hasenstab K, Sugar C, Jeste S, Telesca D, McEvoy K and Senturk D. (2015) Identifying longitudinal trends within EEG experiments. Biometrics, Vol. 71, pp: 1090-1100.

Bayesian Model Decision and Automobile Learning

  • Rossell D., Telesca D. (2017). Non-local priors for high dimensional estimation. JASA, Vol. 112 (517), pp. 254-265 [.pdf]

  • Xu Y., Mueller P., Telesca D. (2016). Bayesian Inference for Latent Biologic Construction with Determinantal Point Precesses (DPP). Biometrics, Vol. 72, pp:955-964.

  • Kim Southward., Scalzo F., Telesca, D. and Hu X. (2015). Ensemble of Sparse Classifiers for High Dimensional Biological Data. Int. J. of Data Mining and Bioinformatics, Vol two, 167-183.

  • Rossell D., Telesca D. and Johnson V.E. (2013). High Dimensional Bayesian Classifiers using Non-local Priors. In Statistical Models for Data Assay, XV: 305-314. Eds. P. Giudici, S. Ingrassia, Thou. Vichy. Springer.

  • Telesca D., Mueller P., Parmigiani G. and Freedman, R.Southward. (2012). Modeling Dependent Cistron Expression. Register of Applied Statistics, half-dozen (2), 542–560.

  • Telesca D., Mueller P., Konrblau S., Suchard M. and Ji Y. (2012). Modeling Protein Expression and Protein Signaling Pathways. JASA, 107, 1372–1384.

Environmental Statistics

  • Watson G.L. Telesca D., Reid C.E., Pfister G. G., Jerrett M. (2019) Machine Learning Models Accurately Predict Ozone Exposure during Wildfire Events. Ecology Pollution, 254, A.

  • Reid C.E., Considine E. Thousand., Watson G. 50., Telesca D, Pfister Chiliad, Jerrett M. (2019). Associations betwixt respiratory wellness and ozone and fine particulate matter during a wildfire effect. Environmental Pollution, 129, pp.291-298.

  • Wing S.East., Bandoli Grand., Telesca D., Su J.Chiliad., Ritz B. (2018). Chronic exposure to inhaled, traffic-related nitrogen dioxide and a blunted cortisol response in adolescents. Ecology Research, 163, pp 201-207.

Nano-Computer science

  • Zaunbrecher C, Beryt E, Parodi D, Telesca D, Doherty J, Malloy T, Allard P, (2017). Has Toxicity Testing Moved into the 21st Century? A Survey and Assay of Perceptions in the Field of Toxicology . Environmental Health Perspectives, 125 (8).

  • Depression-Kam C., Telesca D., Ji Z. X., Zhang H. Y., Nel A. E., Xia T., Zink J. I. (2015). A Bayesian Regression Tree Approach to Place the Effect of Nanoparticle Properties on Toxicity Profiles. The Register of Applied Statistics, Vol. ix, pp: 383-401.

  • Patel T., Telesca D., Low-Kam C., Ji Z-X., Zhang H-Y., Nel A. East., Xia T., Zink J. I. (2014). Relating particle properties to biological outcomes in exposure escalation experiments. Environmetrics, 25 (1), 56–58.

  • Patel T., Telesca D., Rallo R, Xia T, George S. and Nel A. (2013). Hierarchical Rank Aggregation with Applications to Nanotoxicology. JABES, 18 (2), 159–177.

  • Patel T., Telesca D., George South. and Nel A. (2012). Toxicity Profiling of Engineered Nanomaterials via Multivariate Dose Response Surface Modeling. Annals of Applied Statistics, vi (4), 1707–1729.

  • Zhang H., Ji Z., Xia T., Meng H., Depression-Kam C., Liu R., Pokhrel S., Lin S., Wang X., Liao YP., Wang Grand., Li LJ., Rallo R., Damoiseaux R., Telesca D., Madler L., Cohen Y., Zink J., Nel A. (2012). Use of Metal Oxide Nanoparticle Semiconductor Properties and Ring Gap to Develop a Predictive Paradigm for the Oxidative Stress Injury and Acute Toxicological Potential in Cells and the Murine Lung. ACS Nano, 6 (5), 4349–4368.

  • Ivask A, ElBadawy A, Kaweeteerawat C, Boren D, Fischer H, Ji Z, Chang CH, Liu R, Tolaymat T, Telesca D, Zink JI, Cohen Y, Holden PA, Godwin HA. (2014). Toxicity Mechanisms in Escheria coli Vary for Silver Nanoparticles and Differ from Ionic Silver. ACS nano, viii (1), pp 374-386.

High-Dimensional Omics Data

  • Yajima M., Telesca D., Ji Y. and Mueller P. (2015). Detecting Differential Patterns of Interaction in Molecular Pathways. Biostatistics, Vol. 16, pp: 240-251.

  • Telesca D., Mueller P., Parmigiani G. and Freedman, R.S. (2012). Modeling Dependent Factor Expression. Annals of Applied Statistics, 6 (2), 542–560.

  • Telesca D., Mueller P., Konrblau S., Suchard M. and Ji Y. (2012). Modeling Protein Expression and Protein Signaling Pathways. JASA, 107, 1372–1384.

  • Telesca D., Inoue L.Y.T., Neira M., Gleave Chiliad., Nelson C and Etzioni R. (2009). Differential Expression and Network Inferences through Functional Data Modeling. Biometrics, 65, 793–804.

  • Telesca D., Inoue L.Y.T., Neira Thousand., Gleave M., Nelson C and Etzioni R. (2009). Differential Expression and Network Inferences through Functional Data Modeling. Biometrics, 65, 793–804.

Biostatistics in Cancer Epidemiology and Biomarker Discovery

  • Kalbasi A., Kamrava M., Chu F-I, Telesca D., Van Dams R., Yang Y., Ruan D., Nelson S. D., Dry Due south. Thou., Hernandez J., Chmielowski B., Singh A. S., Bukata S. V., Bernthal N.M., Steinberg M.50., Weidhaas J.B., Eilber F.C. (2020). A stage ii trial of 5-solar day neoadjuvant radiotherapy for patients with loftier-take a chance primary soft tissue sarcoma. Clinical Cancer Research, 26 (8), pp 1829-1836.

  • McVeigh TP, Jung SY, Kerin MJ, Salzman DW, Nallur Southward, Nemec AA, Dookwah 1000, Sadofsky J, Paranjape T, Kelly O, Chan E, Miller Northward, Sweeney KJ, Zelterman D, Sweasy J, Pilarski R, Telesca D, Slack FJ, Weidhaas JB. (2015). Estrogen withdrawal, increased breast cancer risk and the KRAS-variant. Prison cell Bike. Vol. 14(13). pp:2091-2099.

  • Yu Due east.Y., Gulati R., Telesca D., Jiang P., Tam S., Russell K.J., Nelson, P.South., Etzioni R.D., and Higano C.South., (2010). Duration of first off treatment interval is prognostic for time to castration resistance and death in men with biochemical relapse of prostate cancer treated on a prospective trial of intermittent androgen impecuniousness. Journal of Clinical Oncology, 28, 16, pp: 2668-2673.

  • Telesca D., Etzioni R. and Gulati R. (2008). Estimating Lead Time and Overdiagnosis Associated with PSA Screening from Prostate Cancer Incidence Trends. Biometrics, 64, ten–19.

Unpublished Technical Reports

  • Yajima G., Telesca D., Rosner G.L., Mueller P. Bayesian modeling of population pharmacogenetics.

  • Zhang Y, Telesca D. Joint clustering and registration of functional data.[arxiv]

  • Zhang Y, Horvath South, Ophoff R, Telesca D. Comparing of Clustering for Time-Grade Genomic Data: Applications to Crumbling Effects. [arxiv]