Grant Number:	5R01CA160736-04 Interpret this number
Primary Investigator:	Baladandayuthapani, Veerabhadran
Organization:	University Of Tx Md Anderson Can Ctr
Project Title:	Integrative Methods for High-Dimensional Genomics Data
Fiscal Year:	2014

DESCRIPTION (provided by applicant): The primary objective of this proposal is to develop adaptive and exible statistical models for analyses of multivariate, functional and spatial data from high-throughput biomedical studies. These studies raise computational, modeling, and inferential challenges with respect to high-dimensionality as well as structured dependency induced by the various aspects of the processes generating the data. Our work is motivated by, and will be applied to, data from a variety of high- throughput cancer-related studies that were conducted by our biomedical collaborators, in genomics, epigenomics and transcriptomics; although our methods are generally applicable to other contexts. The short-term objective of this research is to develop novel statistical methods and computational tools for statistical and probabilistic modeling of such high-throughput data with particular emphasis on integrative methods to combine information within and across dierent assays as well as clinical data to answer important biological questions. Our long-term goal is to improve risk prediction and treatment selection in cancer prevention, diagnosis and prognosis. We will accomplish the objective of this application by pursuing the following ve specic aims (1) develop new methodology for Bayesian adaptive generalized functional linear mixed models, allowing for local and nonlinear association structures between scalar responses and functional predictors (2) develop hierarchical Bayesian joint models for integrating diverse types of multivariate and functional data. (3) develop Bayesian spatial-functional process models for spatially indexed high-dimensional functional data, methods for data requiring a broader class of within-function and between-function covariance structures using exible families of covariance functions. (4) develop multivariate Bayesian spatial-functional models for joint modeling of multiple spatially indexed functional data. (5) develop ecient, user-friendly and freely available software for the proposed methods.




Tumor radiogenomics in gliomas with Bayesian layered variable selection.
Authors: Mohammed S. , Kurtek S. , Bharath K. , Rao A. , Baladandayuthapani V. .
Source: Medical Image Analysis, 2023 Dec; 90, p. 102964.
EPub date: 2023-09-12 00:00:00.0.
PMID: 37797481
Related Citations

BaySyn: Bayesian Evidence Synthesis for Multi-system Multiomic Integration.
Authors: Bhattacharyya R. , Henderson N. , Baladandayuthapani V. .
Source: Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, 2023; 28, p. 275-286.
PMID: 36540984
Related Citations

Role of multiresolution vulnerability indices in COVID-19 spread in India: a Bayesian model-based analysis.
Authors: Bhattacharyya R. , Burman A. , Singh K. , Banerjee S. , Maity S. , Auddy A. , Rout S.K. , Lahoti S. , Panda R. , Baladandayuthapani V. .
Source: Bmj Open, 2022-11-17 00:00:00.0; 12(11), p. e056292.
EPub date: 2022-11-17 00:00:00.0.
PMID: 36396323
Related Citations

SpaceX: gene co-expression network estimation for spatial transcriptomics.
Authors: Acharyya S. , Zhou X. , Baladandayuthapani V. .
Source: Bioinformatics (oxford, England), 2022-11-15 00:00:00.0; 38(22), p. 5033-5041.
PMID: 36179087
Related Citations

NetCellMatch: Multiscale Network-Based Matching of Cancer Cell Lines to Patients Using Graphical Wavelets.
Authors: Desai N. , Morris J.S. , Baladandayuthapani V. .
Source: Chemistry & Biodiversity, 2022-10-24 00:00:00.0; , p. e202200746.
EPub date: 2022-10-24 00:00:00.0.
PMID: 36279370
Related Citations

Bayesian hierarchical quantile regression with application to characterizing the immune architecture of lung cancer.
Authors: Das P. , Peterson C.B. , Ni Y. , Reuben A. , Zhang J. , Zhang J. , Do K.A. , Baladandayuthapani V. .
Source: Biometrics, 2022-10-14 00:00:00.0; , .
EPub date: 2022-10-14 00:00:00.0.
PMID: 36239535
Related Citations

Integrative Bayesian models using Post-selective inference: A case study in radiogenomics.
Authors: Panigrahi S. , Mohammed S. , Rao A. , Baladandayuthapani V. .
Source: Biometrics, 2022-08-16 00:00:00.0; , .
EPub date: 2022-08-16 00:00:00.0.
PMID: 35973786
Related Citations

Bayesian graphical models for modern biological applications.
Authors: Ni Y. , Baladandayuthapani V. , Vannucci M. , Stingo F.C. .
Source: Statistical Methods & Applications, 2022; 31(2), p. 197-225.
EPub date: 2021-05-27 00:00:00.0.
PMID: 35673326
Related Citations

Bayesian Edge Regression in Undirected Graphical Models to Characterize Interpatient Heterogeneity in Cancer.
Authors: Wang Z. , Kaseb A.O. , Amin H.M. , Hassan M.M. , Wang W. , Morris J.S. .
Source: Journal Of The American Statistical Association, 2022; 117(538), p. 533-546.
EPub date: 2022-01-05 00:00:00.0.
PMID: 36090952
Related Citations

Bayesian Structure Learning in Multi-layered Genomic Networks.
Authors: Ha M.J. , Stingo F.C. , Baladandayuthapani V. .
Source: Journal Of The American Statistical Association, 2021; 116(534), p. 605-618.
EPub date: 2020-07-24 00:00:00.0.
PMID: 34239216
Related Citations

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome.
Authors: Bhattacharyya R. , Ha M.J. , Liu Q. , Akbani R. , Liang H. , Baladandayuthapani V. .
Source: Jco Clinical Cancer Informatics, 2020 May; 4, p. 399-411.
PMID: 32374631
Related Citations

Imaging-Based Algorithm for the Local Grading of Glioma.
Authors: Gates E.D.H. , Lin J.S. , Weinberg J.S. , Prabhu S.S. , Hamilton J. , Hazle J.D. , Fuller G.N. , Baladandayuthapani V. , Fuentes D.T. , Schellingerhout D. .
Source: Ajnr. American Journal Of Neuroradiology, 2020 Mar; 41(3), p. 400-407.
EPub date: 2020-02-06 00:00:00.0.
PMID: 32029466
Related Citations

NExUS: Bayesian simultaneous network estimation across unequal sample sizes.
Authors: Das P. , Peterson C.B. , Do K.A. , Akbani R. , Baladandayuthapani V. .
Source: Bioinformatics (oxford, England), 2020-02-01 00:00:00.0; 36(3), p. 798-804.
PMID: 31504175
Related Citations

Network-Based Matching of Patients and Targeted Therapies for Precision Oncology.
Authors: Liu Q. , Ha M.J. , Bhattacharyya R. , Garmire L. , Baladandayuthapani V. .
Source: Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, 2020; 25, p. 623-634.
PMID: 31797633
Related Citations

Quantile Function on Scalar Regression Analysis for Distributional Data.
Authors: Yang H. , Baladandayuthapani V. , Rao A.U.K. , Morris J.S. .
Source: Journal Of The American Statistical Association, 2020; 115(529), p. 90-106.
EPub date: 2019-06-21 00:00:00.0.
PMID: 32981991
Related Citations

Bayesian data integration and variable selection for pan-cancer survival prediction using protein expression data.
Authors: Maity A.K. , Bhattacharya A. , Mallick B.K. , Baladandayuthapani V. .
Source: Biometrics, 2019-08-08 00:00:00.0; , .
EPub date: 2019-08-08 00:00:00.0.
PMID: 31393003
Related Citations

Efficient Bayesian Regularization for Graphical Model Selection.
Authors: Kundu S. , Mallick B.K. , Baladandayuthapan V. .
Source: Bayesian Analysis, 2019 Jun; 14(2), p. 449-476.
EPub date: 2018-07-11 00:00:00.0.
PMID: 33123305
Related Citations

Spectral Clustering via sparse graph structure learning with application to Proteomic Signaling Networks in Cancer.
Authors: Banerjee S. , Akbani R. , Baladandayuthapani V. .
Source: Computational Statistics & Data Analysis, 2019 Apr; 132, p. 46-69.
EPub date: 2018-08-23 00:00:00.0.
PMID: 38774121
Related Citations

Bayesian Hierarchical Varying-sparsity Regression Models with Application to Cancer Proteogenomics.
Authors: Ni Y. , Stingo F.C. , Ha M.J. , Akbani R. , Baladandayuthapani V. .
Source: Journal Of The American Statistical Association, 2019; 114(525), p. 48-60.
EPub date: 2018-08-15 00:00:00.0.
PMID: 31178611
Related Citations

Bayesian Semiparametric Functional Mixed Models for Serially Correlated Functional Data, with Application to Glaucoma Data.
Authors: Lee W. , Miranda M.F. , Rausch P. , Baladandayuthapani V. , Fazio M. , Downs J.C. , Morris J.S. .
Source: Journal Of The American Statistical Association, 2019; 114(526), p. 495-513.
EPub date: 2018-08-15 00:00:00.0.
PMID: 31235987
Related Citations

RADIO-IBAG: RADIOMICS-BASED INTEGRATIVE BAYESIAN ANALYSIS OF MULTIPLATFORM GENOMIC DATA.
Authors: Zhang Y. , Morris J.S. , Aerry S.N. , Rao A.U.K. , Baladandayuthapani V. .
Source: The Annals Of Applied Statistics, 2019; 13(3), p. 1957-1988.
EPub date: 2019-10-17 00:00:00.0.
PMID: 33224404
Related Citations

Bayesian Graphical Regression.
Authors: Ni Y. , Stingo F.C. , Baladandayuthapani V. .
Source: Journal Of The American Statistical Association, 2019; 114(525), p. 184-197.
EPub date: 2018-06-28 00:00:00.0.
PMID: 36937091
Related Citations

Personalized Integrated Network Modeling of the Cancer Proteome Atlas.
Authors: Ha M.J. , Banerjee S. , Akbani R. , Liang H. , Mills G.B. , Do K.A. , Baladandayuthapani V. .
Source: Scientific Reports, 2018-10-08 00:00:00.0; 8(1), p. 14924.
EPub date: 2018-10-08 00:00:00.0.
PMID: 30297783
Related Citations

Functional interaction-based nonlinear models with application to multiplatform genomics data.
Authors: Davenport C.A. , Maity A. , Baladandayuthapani V. .
Source: Statistics In Medicine, 2018-05-07 00:00:00.0; , .
EPub date: 2018-05-07 00:00:00.0.
PMID: 29737021
Related Citations

iDINGO-integrative differential network analysis in genomics with Shiny application.
Authors: Class C.A. , Ha M.J. , Baladandayuthapani V. , Do K.A. .
Source: Bioinformatics (oxford, England), 2018-04-01 00:00:00.0; 34(7), p. 1243-1245.
PMID: 29194470
Related Citations

Dissecting Pathway Disturbances Using Network Topology and Multi-platform Genomics Data.
Authors: Zhang Y. , Linder M.H. , Shojaie A. , Ouyang Z. , Shen R. , Baggerly K.A. , Baladandayuthapani V. , Zhao H. .
Source: Statistics In Biosciences, 2018 Apr; 10(1), p. 86-106.
EPub date: 2017-05-04 00:00:00.0.
PMID: 37388623
Related Citations

Tree-based Methods for Characterizing Tumor Density Heterogeneity.
Authors: Shoemaker K. , Hobbs B.P. , Bharath K. , Ng C.S. , Baladandayuthapani V. .
Source: Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing, 2018; 23, p. 216-227.
PMID: 29218883
Related Citations

Bayesian variable selection with graphical structure learning: Applications in integrative genomics.
Authors: Kundu S. , Cheng Y. , Shin M. , Manyam G. , Mallick B.K. , Baladandayuthapani V. .
Source: Plos One, 2018; 13(7), p. e0195070.
EPub date: 2018-07-30 00:00:00.0.
PMID: 30059495
Related Citations

Integrating Clinical and Multiple Omics Data for Prognostic Assessment across Human Cancers.
Authors: Zhu B. , Song N. , Shen R. , Arora A. , Machiela M.J. , Song L. , Landi M.T. , Ghosh D. , Chatterjee N. , Baladandayuthapani V. , et al. .
Source: Scientific Reports, 2017-12-05 00:00:00.0; 7(1), p. 16954.
EPub date: 2017-12-05 00:00:00.0.
PMID: 29209073
Related Citations

Radiomic analysis in prediction of Human Papilloma Virus status.
Authors: Yu K. , Zhang Y. , Yu Y. , Huang C. , Liu R. , Li T. , Yang L. , Morris J.S. , Baladandayuthapani V. , Zhu H. .
Source: Clinical And Translational Radiation Oncology, 2017 Dec; 7, p. 49-54.
EPub date: 2017-11-06 00:00:00.0.
PMID: 29594229
Related Citations

Rejoinder to statistical contributions to bioinformatics: Design, modelling, structure learning and Integration.
Authors: Morris J.S. , Baladandayuthapani V. .
Source: Statistical Modelling, 2017 Aug; 17(4-5), p. 338-357.
EPub date: 2017-09-12 00:00:00.0.
PMID: 30034293
Related Citations

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.
Authors: Kim S. , Baladandayuthapani V. , Lee J.J. .
Source: Statistics In Biosciences, 2017 Jun; 9(1), p. 217-245.
EPub date: 2016-09-26 00:00:00.0.
PMID: 28785367
Related Citations

Inferring network structure in non-normal and mixed discrete-continuous genomic data.
Authors: Bhadra A. , Rao A. , Baladandayuthapani V. .
Source: Biometrics, 2017-04-24 00:00:00.0; , .
EPub date: 2017-04-24 00:00:00.0.
PMID: 28437848
Related Citations

Statistical Contributions to Bioinformatics: Design, Modeling, Structure Learning, and Integration.
Authors: Morris J.S. , Baladandayuthapani V. .
Source: Statistical Modelling, 2017; 17(4-5), p. 245-289.
EPub date: 2017-06-15 00:00:00.0.
PMID: 29129969
Related Citations

STATISTICAL TESTS FOR LARGE TREE-STRUCTURED DATA.
Authors: Bharath K. , Kambadur P. , Dey D.K. , Rao A. , Baladandayuthapani V. .
Source: Journal Of The American Statistical Association, 2017; 112(520), p. 1733-1743.
EPub date: 2017-08-07 00:00:00.0.
PMID: 37013199
Related Citations

A semiparametric Bayesian model for comparing DNA copy numbers.
Authors: Nieto-Barajas L. , Ji Y. , Baladandayuthapani V. .
Source: Brazilian Journal Of Probability And Statistics, 2016 Aug; 30(3), p. 345-365.
EPub date: 2016-07-29 00:00:00.0.
PMID: 37799327
Related Citations

Association Of Cpg Island Methylator Phenotype And Ereg/areg Methylation And Expression In Colorectal Cancer
Authors: Lee M.S. , McGuffey E.J. , Morris J.S. , Manyam G. , Baladandayuthapani V. , Wei W. , Morris V.K. , Overman M.J. , Maru D.M. , Jiang Z.Q. , et al. .
Source: British Journal Of Cancer, 2016-06-14 00:00:00.0; 114(12), p. 1352-61.
PMID: 27272216
Related Citations

Pcan: Probabilistic Correlation Analysis Of Two Non-normal Data Sets
Authors: Zoh R.S. , Mallick B. , Ivanov I. , Baladandayuthapani V. , Manyam G. , Chapkin R.S. , Lampe J.W. , Carroll R.J. .
Source: Biometrics, 2016-04-01 00:00:00.0; , .
PMID: 27037601
Related Citations

INTEGRATIVE BAYESIAN ANALYSIS OF NEUROIMAGING-GENETIC DATA THROUGH HIERARCHICAL DIMENSION REDUCTION.
Authors: Azadeh S. , Hobbs B.P. , Ma L. , Nielsen D.A. , Moeller F.G. , Baladandayuthapani V. .
Source: Proceedings. Ieee International Symposium On Biomedical Imaging, 2016 Apr; 2016, p. 824-828.
EPub date: 2016-06-16 00:00:00.0.
PMID: 27917260
Related Citations

Identification of differentially methylated loci using wavelet-based functional mixed models.
Authors: Lee W. , Morris J.S. .
Source: Bioinformatics (oxford, England), 2016-03-01 00:00:00.0; 32(5), p. 664-72.
EPub date: 2016-03-01 00:00:00.0.
PMID: 26559505
Related Citations

Integrative Bayesian Analysis Of Neuroimaging-genetic Data With Application To Cocaine Dependence
Authors: Azadeh S. , Hobbs B.P. , Ma L. , Nielsen D.A. , Moeller F.G. , Baladandayuthapani V. .
Source: Neuroimage, 2016-01-15 00:00:00.0; 125, p. 813-24.
PMID: 26484829
Related Citations

Detection and Quantification of Protein Spots by Pinnacle.
Authors: Morris J.S. , Gutstein H.B. .
Source: Methods In Molecular Biology (clifton, N.j.), 2016; 1384, p. 185-201.
PMID: 26611416
Related Citations

Demarcate: Density-based Magnetic Resonance Image Clustering For Assessing Tumor Heterogeneity In Cancer
Authors: Saha A. , Banerjee S. , Kurtek S. , Narang S. , Lee J. , Rao G. , Martinez J. , Bharath K. , Rao A.U. , Baladandayuthapani V. .
Source: Neuroimage. Clinical, 2016; 12, p. 132-43.
PMID: 27408798
Related Citations

Functional Car Models For Large Spatially Correlated Functional Datasets
Authors: Zhang L. , Baladandayuthapani V. , Zhu H. , Baggerly K.A. , Majewski T. , Czerniak B.A. , Morris J.S. .
Source: Journal Of The American Statistical Association, 2016; 111(514), p. 772-786.
PMID: 28018013
Related Citations

Dingo: Differential Network Analysis In Genomics
Authors: Ha M.J. , Baladandayuthapani V. , Do K.A. .
Source: Bioinformatics (oxford, England), 2015-11-01 00:00:00.0; 31(21), p. 3413-20.
PMID: 26148744
Related Citations

Bayesian function-on-function regression for multilevel functional data.
Authors: Meyer M.J. , Coull B.A. , Versace F. , Cinciripini P. , Morris J.S. .
Source: Biometrics, 2015 Sep; 71(3), p. 563-74.
PMID: 25787146
Related Citations

Bayesian Nonlinear Model Selection For Gene Regulatory Networks
Authors: Ni Y. , Stingo F.C. , Baladandayuthapani V. .
Source: Biometrics, 2015 Sep; 71(3), p. 585-95.
PMID: 25854759
Related Citations

A Two-sample Test For Equality Of Means In High Dimension
Authors: Gregory K.B. , Carroll R.J. , Baladandayuthapani V. , Lahiri S.N. .
Source: Journal Of The American Statistical Association, 2015-06-01 00:00:00.0; 110(510), p. 837-849.
PMID: 26279594
Related Citations

Prognostic Gene Signature Identification Using Causal Structure Learning: Applications In Kidney Cancer
Authors: Ha M.J. , Baladandayuthapani V. , Do K.A. .
Source: Cancer Informatics, 2015; 14(Suppl 1), p. 23-35.
PMID: 25861215
Related Citations

Latent Feature Decompositions For Integrative Analysis Of Multi-platform Genomic Data
Authors: Gregory K.B. , Momin A.A. , Coombes K.R. , Baladandayuthapani V. .
Source: Ieee/acm Transactions On Computational Biology And Bioinformatics / Ieee, Acm, 2014 Nov-Dec; 11(6), p. 984-94.
PMID: 26146492
Related Citations