Veerabhadran Baladandayuthapani

发表

Bani K. Mallick, David Lee Gold, Veerabhadran Baladandayuthapani, 2009 .

A fast convergence clustering algorithm merging MCMC and EM methods

Carlos Ordonez, Veerabhadran Baladandayuthapani, David Sergio Matusevich, 2013, CIKM.

Bayesian Nonparametric Differential Analysis for Dependent Multigroup Data with Application to Colorectal Cancer DNA Methylation

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Subharup Guha, 2017 .

Integrative sparse Bayesian analysis of high-dimensional multi-platform genomic data in glioblastoma

Veerabhadran Baladandayuthapani, Anindya Bhadra, 2013, 2013 IEEE International Workshop on Genomic Signal Processing and Statistics.

Integrative analysis of multi-modal correlated imaging-genomics data in glioblastoma

Jeffrey S. Morris, Arvind U. K. Rao, Veerabhadran Baladandayuthapani, 2013, 2013 IEEE International Workshop on Genomic Signal Processing and Statistics.

Bayesian variable selection with graphical structure learning: Applications in integrative genomics

Yichen Cheng, Veerabhadran Baladandayuthapani, Bani K Mallick, 2018, PloS one.

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome

Veerabhadran Baladandayuthapani, Rehan Akbani, Rupam Bhattacharyya, 2020, JCO clinical cancer informatics.

Appendix A: Basics of Bayesian Modeling

Bani K. Mallick, David Lee Gold, Veerabhadran Baladandayuthapani, 2009 .

Latent Feature Decompositions for Integrative Analysis of Multi-Platform Genomic Data

Veerabhadran Baladandayuthapani, Kevin R. Coombes, Karl B. Gregory, 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Unsupervised Classification and Bayesian Clustering

Bani K. Mallick, David Lee Gold, Veerabhadran Baladandayuthapani, 2009 .

Integrative network-based Bayesian analysis of diverse genomics data

Kim-Anh Do, Veerabhadran Baladandayuthapani, Wenting Wang, 2013, BMC Bioinformatics.

Nonparametric Variable Selection, Clustering and Prediction for Large Biological Datasets

Veerabhadran Baladandayuthapani, Subharup Guha, Chiyu Gu, 2015 .

Spectral clustering via sparse graph structure learning with application to proteomic signaling networks in cancer

Veerabhadran Baladandayuthapani, Rehan Akbani, Sayantan Banerjee, 2019, Comput. Stat. Data Anal..

Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSiPS 2012, Washington, DC, USA, December 2-4, 2012

Wenyi Wang, Peng Qiu, Jinlian Wang, 2012, GENSiPS.

Bayesian Variable Selection in Linear Regression in One Pass for Large Datasets

Carlos Ordonez, Carlos Garcia-Alvarado, Veerabhadran Baladandayuthapani, 2014, TKDD.

Bayesian nonlinear model selection for gene regulatory networks

Francesco C Stingo, Yang Ni, Veerabhadran Baladandayuthapani, 2015, Biometrics.

AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Jeffrey S Morris, 2011, The annals of applied statistics.

Data mining algorithms as a service in the cloud exploiting relational database systems

Wellington Cabrera, Carlos Garcia-Alvarado, Carlos Ordonez, 2013, SIGMOD '13.

Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms.

Daniel Barker, Veerabhadran Baladandayuthapani, Shariq Mohammed, 2020, Harvard data science review.

RADIO-IBAG: RADIOMICS-BASED INTEGRATIVE BAYESIAN ANALYSIS OF MULTIPLATFORM GENOMIC DATA.

Jeffrey S. Morris, Arvind U. K. Rao, Veerabhadran Baladandayuthapani, 2019, The annals of applied statistics.

Querying external source code files of programs connecting to a relational database

Carlos Garcia-Alvarado, Carlos Ordonez, Veerabhadran Baladandayuthapani, 2012, PIKM '12.

Bayesian Graphical Models

Bani K. Mallick, David Lee Gold, Veerabhadran Baladandayuthapani, 2009 .

Prognostic Gene Signature Identification Using Causal Structure Learning: Applications in Kidney Cancer

Kim-Anh Do, Veerabhadran Baladandayuthapani, Min Jin Ha, 2015, Cancer informatics.

Rejoinder to statistical contributions to bioinformatics: Design, modelling, structure learning and Integration

Veerabhadran Baladandayuthapani, Jeffrey S Morris, 2017, Statistical modelling.

BAYESIAN SPARSE GRAPHICAL MODELS FOR CLASSIFICATION WITH APPLICATION TO PROTEIN EXPRESSION DATA.

Yuan Ji, Yiling Lu, Veerabhadran Baladandayuthapani, 2014, The annals of applied statistics.

Bayesian data integration and variable selection for pan‐cancer survival prediction using protein expression data

Veerabhadran Baladandayuthapani, Bani K Mallick, Anirban Bhattacharya, 2019, Biometrics.

Tree-based Methods for Characterizing Tumor Density Heterogeneity

Veerabhadran Baladandayuthapani, Karthik Bharath, Chaan S. Ng, 2017, PSB.

Bayesian sparse graphical models and their mixtures

Veerabhadran Baladandayuthapani, Bani K Mallick, Rajesh Talluri, 2014, Stat.

Hierarchical Bayesian methods for integration of various types of genomics data

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Raymond J. Carroll, 2012, Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS).

Bayesian Variable Selection in Multivariate Nonlinear Regression with Graph Structures

Bani K. Mallick, Veerabhadran Baladandayuthapani, Nilabja Guha, 2020, 2010.14638.

DINGO: differential network analysis in genomics

Kim-Anh Do, Veerabhadran Baladandayuthapani, Min Jin Ha, 2015, Bioinform..

Functional interaction–based nonlinear models with application to multiplatform genomics data

Arnab Maity, Veerabhadran Baladandayuthapani, Clemontina A Davenport, 2018, Statistics in medicine.

Bayesian Analysis of Gene Expression Data

Bani K. Mallick, David Lee Gold, Veerabhadran Baladandayuthapani, 2009 .

Integrative Bayesian models using Post‐selective inference: A case study in radiogenomics

Veerabhadran Baladandayuthapani, Arvind Rao, Shariq Mohammed, 2020, Biometrics.

Bayesian Structure Learning in Multi-layered Genomic Networks.

Veerabhadran Baladandayuthapani, Min Jin Ha, Francesco Stingo, 2020 .

Bayesian Random Segmentation Models to Identify Shared Copy Number Aberrations for Array CGH Data

Jeffrey S. Morris, Yuan Ji, Veerabhadran Baladandayuthapani, 2010, Journal of the American Statistical Association.

Integrative Bayesian analysis of neuroimaging-genetic data through hierarchical dimension reduction

Veerabhadran Baladandayuthapani, Liangsuo Ma, Brian P. Hobbs, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Bayesian methods for expression-based integration of various types of genomics data

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Raymond J. Carroll, 2013, EURASIP J. Bioinform. Syst. Biol..

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Wenyi Wang, Veerabhadran Baladandayuthapani, Pascal O. Zinn, 2012, GENSiPS.

Bayesian ensemble methods for survival prediction in gene expression data

Kim-Anh Do, Veerabhadran Baladandayuthapani, Vinícius Bonato, 2011, Bioinform..

Integrative Bayesian analysis of neuroimaging-genetic data with application to cocaine dependence

Veerabhadran Baladandayuthapani, Liangsuo Ma, Brian P. Hobbs, 2016, NeuroImage.

Personalized Integrated Network Modeling of the Cancer Proteome Atlas

Veerabhadran Baladandayuthapani, Rehan Akbani, Han Liang, 2018, Scientific Reports.

Bayesian approaches for large biological networks

Yang Ni, Veerabhadran Baladandayuthapani, Giovanni M. Marchetti, 2015 .

Statistical contributions to bioinformatics: Design, modelling, structure learning and integration

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Jeffrey S Morris, 2017, Statistical modelling.

iDINGO—integrative differential network analysis in genomics with Shiny application

Kim-Anh Do, Veerabhadran Baladandayuthapani, Min Jin Ha, 2017, Bioinform..

Bayesian models for flexible integrative analysis of multi-platform genomics data

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Raymond J. Carroll, 2015 .

Bayesian hierarchical structured variable selection methods with application to molecular inversion probe studies in breast cancer

Lin Zhang, Bani K. Mallick, Kim-Anh Do, 2014 .

NExUS: Bayesian simultaneous network estimation across unequal sample sizes

Kim-Anh Do, Veerabhadran Baladandayuthapani, Rehan Akbani, 2018, Bioinform..

Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges

G. Elisabeta Marai, John Freymann, Carlo Sansone, 2018, Front. Oncol..

Inferring network structure in non‐normal and mixed discrete‐continuous genomic data

Veerabhadran Baladandayuthapani, Anindya Bhadra, Arvind Rao, 2016, Biometrics.

Bayesian variable selection for linear regression in high dimensional microarray data

Wellington Cabrera, Carlos Ordonez, Veerabhadran Baladandayuthapani, 2013, DTMBIO '13.

Latent feature decompositions for integrative analysis of diverse high-throughput genomic data

Michael Peyton, John D. Minna, Veerabhadran Baladandayuthapani, 2012, Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS).

On the Computation of Stochastic Search Variable Selection in Linear Regression with UDFs

Carlos Ordonez, Veerabhadran Baladandayuthapani, Mario Navas, 2010, 2010 IEEE International Conference on Data Mining.

iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data

Jeffrey S. Morris, Kim-Anh Do, Veerabhadran Baladandayuthapani, 2012, Bioinform..

Bayesian methods in bioinformatics

Veerabhadran Baladandayuthapani, 2007 .

Integrating multi-platform genomic data using hierarchical Bayesian relevance vector machines

Wenyi Wang, Carlos Ordonez, Veerabhadran Baladandayuthapani, 2012, Proceedings 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS).

Tumor Radiogenomics with Bayesian Layered Variable Selection

Sebastian Kurtek, Veerabhadran Baladandayuthapani, Karthik Bharath, 2021, 2106.10941.

Bayesian Robust Learning in Chain Graph Models for Integrative Pharmacogenomics

Veerabhadran Baladandayuthapani, Anindya Bhadra, Min Jin Ha, 2021, 2111.11529.

Bayesian graphical models for modern biological applications

Marina Vannucci, Yang Ni, Veerabhadran Baladandayuthapani, 2021, Statistical Methods & Applications.

RADIOHEAD: Radiogenomic analysis incorporating tumor heterogeneity in imaging through densities

Sebastian Kurtek, Veerabhadran Baladandayuthapani, Karthik Bharath, 2021, The Annals of Applied Statistics.

Bayesian Structure Learning in Multilayered Genomic Networks

Veerabhadran Baladandayuthapani, Min Jin Ha, Francesco Claudio Stingo, 2020, Journal of the American Statistical Association.

Reduced Rank Mixed Effects Models for Spatially Correlated Hierarchical Functional Data

Arnab Maity, Jianhua Z. Huang, Veerabhadran Baladandayuthapani, 2010, Journal of the American Statistical Association.

Radiologic image‐based statistical shape analysis of brain tumours

Sebastian Kurtek, Veerabhadran Baladandayuthapani, Karthik Bharath, 2017, Journal of the Royal Statistical Society. Series C, Applied statistics.

Bayesian Joint Selection of Genes and Pathways: Applications in Multiple Myeloma Genomics

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Jeffrey S Morris, 2014, Cancer informatics.

Network-Based Matching of Patients and Targeted Therapies for Precision Oncology

Veerabhadran Baladandayuthapani, Lana X. Garmire, Rupam Bhattacharyya, 2019, bioRxiv.

Bayesian Graphical Regression

Yang Ni, Veerabhadran Baladandayuthapani, Francesco C. Stingo, 2018, Journal of the American Statistical Association.

Bayesian sparse graphical models and their mixtures using lasso selection priors

Bani K. Mallick, Veerabhadran Baladandayuthapani, Rajesh Talluri, 2013 .

Spatial modeling of annual minimum and maximum temperatures in Iceland

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Birgir Hrafnkelsson, 2012, Meteorology and Atmospheric Physics.

Bayes Factors Based on Test Statistics Under Order Restrictions

Valen E. Johnson, Veerabhadran Baladandayuthapani, David Rossell, 2008 .

A Two-Sample Test for Equality of Means in High Dimension

Veerabhadran Baladandayuthapani, Raymond J. Carroll, Soumendra N. Lahiri, 2015, Journal of the American Statistical Association.

Selective Genomic Copy Number Imbalances and Probability of Recurrence in Early-Stage Breast Cancer

Mary E. Edgerton, Veerabhadran Baladandayuthapani, Gordon B. Mills, 2011, PloS one.

Spatially Adaptive Bayesian Penalized Regression Splines (P-splines)

Veerabhadran Baladandayuthapani, Raymond J Carroll, Bani K Mallick, 2005 .

Bayesian disease classification using copy number data.

Yuan Ji, Veerabhadran Baladandayuthapani, Subharup Guha, 2014, Cancer informatics.

Sparse Multi-Dimensional Graphical Models: A Unified Bayesian Framework

Yang Ni, Veerabhadran Baladandayuthapani, Francesco C. Stingo, 2017 .

Inference for Large Tree-structured Data

Prabhanjan Kambadur, Veerabhadran Baladandayuthapani, Karthik Bharath, 2014, 1404.2910.

Radiomic analysis in prediction of Human Papilloma Virus status

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Tengfei Li, 2017, Clinical and translational radiation oncology.

Functional CAR Models for Large Spatially Correlated Functional Datasets

Jeffrey S. Morris, Veerabhadran Baladandayuthapani, Hongxiao Zhu, 2016, Journal of the American Statistical Association.