Vanathi Gopalakrishnan, PhD

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks.

Ceschin R, Zahner A, Reynolds W, Gaesser J, Zuccoli G, Lo CW, Gopalakrishnan V, Panigrahy A. A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks. Neuroimage. 2018 Sep;178:183-197. doi: 10.1016/j.neuroimage.2018.05.049. Epub 2018 May 21. PMID: 29793060.

Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery

Balasubramanian JB, Gopalakrishnan V. Tunable structure priors for Bayesian rule learning for knowledge integrated biomarker discovery. World J Clin Oncol. 2018 Sep 14;9(5): 89-109. doi: 10.5306/wjco.v9.i5.98.

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure

Lustgarten JL, Balasubramanian JB, Visweswaran S, Gopalakrishnan V, Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure. Data (Basel).  2017 Mar;2(1). pii: 5. Epub 2017 Jan 18. PMID: 28331847.  PMCID: PMC5358670.  DOI: 10.3390/data2010005.

An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data

Liu Y, Gopalakrishnan V. An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data. Data 2017, 2(1), 8; doi: 10.3390/data2010008.

On Predicting lung cancer subtypes using 'omic' data from tumor and tumor-adjacent histologically-normal tissue

Pineda AL, Ogoe HA, Balasubramanian JB, Rangel Escareño C, Visweswaran S, Herman JG, Gopalakrishnan V. On Predicting lung cancer subtypes using 'omic' data from tumor and tumor-adjacent histologically-normal tissue. BMC Cancer. 2016 Mar 4;16:184. doi: 10.1186/s12885-016-2223-3. PMID:  26944944  PMCID:  PMC4778315  DOI: 10.1186/s12885-016-2223-3.

Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations

Torbati ME, Mitreva M, Gopalakrishnan V. Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations.  2016 Dec;1(3). pii: 19. doi: 10.3390/data1030019. Epub 2016 Dec 13.    PMID: 28239609  PMCID: PMC5325162  DOI: 10.3390/data1030019
 

cMRI-BED: A novel informatics framework for cardiac MRI biomarker extraction and discovery applied to pediatric cardiomyopathy classification.

Gopalakrishnan V, Menon PG, Madan S., cMRI-BED: A novel informatics framework for cardiac MRI biomarker extraction and discovery applied to pediatric cardiomyopathy classification. Biomed Eng Online. 2015;14 Suppl 2:S7. doi: 10.1186/1475-925X-14-S2-S7. Epub 2015 Aug 13. PMID: 26329721 PMCID: PMC4547147 DOI: 10.1186/1475-925X-14-S2-S7
 

Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data

Ogoe, HA, Visweswaran, S, Lu, X, Gopalakrishnan, V.  (2015) Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data.  BMC Bioinformatics 16:226 (designated as a Highly Accessed paper) PMID: 26202217 PMCID: PMC4512094

Novel Application of Junction Trees to the Interpretation of Epigenetic Differences among Lung Cancer Subtypes

Pineda, AL, Gopalakrishnan, V. Novel Application of Junction Trees to the Interpretation of Epigenetic Differences among Lung Cancer Subtypes. Proceedings of the AMIA Translational Bioinformatics Summit. March 21-23, 2015. PMID: 26306226   Winner of the Marco Ramoni Distinguished Paper Award.

Sfdm: Open-source software for temporal analysis and visualization of brain tumor diffusion mr using serial functional diffusion mapping

R. Ceschin, A. Panigrahy, and V. Gopalakrishnan, “Sfdm: Open-source software for temporal analysis and visualization of brain tumor diffusion mr using serial functional diffusion mapping,” Cancer Inform., vol. 14, pp. 1–9, 2015. PMID: 25673970 PMCID: PMC4315050 DOI: 10.4137/CIN.S17293

^