The Crystallographer's Assistant. - Vanathi Gopalakrishnan; Daniel N. Hennessy; Bruce G. Buchanan; Devika Subramanian (AAAI, 1994)

Induction of Rules for Biological Macromolecular Crystallization. - Daniel N. Hennessy; Vanathi Gopalakrishnan; Bruce G. Buchanan; John M. Rosenberg; Devika Subramanian (ISMB, 1994)

Inducing Design Biases that Characterize Successful Experimentation in Weak-Theory Domains: TIPS. - Vanathi Gopalakrishnan (AAAI/IAAI, Vol. 2, 1996)

Representing and Learning Temporal Relationships among Experimental Variables. - Vanathi Gopalakrishnan; Bruce G. Buchanan (TIME, 1998)

Intelligent Aids for Parallel Experiment Planning and Macromolecular Crystallization. - Vanathi Gopalakrishnan; Bruce G. Buchanan; John M. Rosenberg (ISMB, 2000)

Context sensitive vocabulary and its application in protein secondary structure prediction. - Yan Liu 002; Jaime G. Carbonell; Judith Klein-Seetharaman; Vanathi Gopalakrishnan (SIGIR, 2004)

Comparison of probabilistic combination methods for protein secondary structure prediction. - Yan Liu 002; Jaime G. Carbonell; Judith Klein-Seetharaman; Vanathi Gopalakrishnan (Bioinform., 2004)

Automatic annotation of protein motif function with Gene Ontology terms. - Xinghua Lu 001; Chengxiang Zhai; Vanathi Gopalakrishnan; Bruce G. Buchanan (BMC Bioinform., 2004)

Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition. - Yan Liu 002; Jaime G. Carbonell; Peter Weigele; Vanathi Gopalakrishnan (RECOMB, 2005)

Segmentation of fMRI Data by Maximization of Region Contrast. - Pinaki S. Mitra; Vanathi Gopalakrishnan; Rebecca L. McNamee (CVPR Workshops, 2006)

Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra. - Vanathi Gopalakrishnan; Philip Ganchev; Srikanth Ranganathan; Robert P. Bowser (BioDM, 2006)

Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs). - Yan Liu 002; Jaime G. Carbonell; Peter Weigele; Vanathi Gopalakrishnan (J. Comput. Biol., 2006)

Protein Quaternary Fold Recognition Using Conditional Graphical Models. - Yan Liu 002; Jaime G. Carbonell; Vanathi Gopalakrishnan; Peter Weigele (IJCAI, 2007)

Improving Classification Performance with Discretization on Biomedical Datasets. - Jonathan L. Lustgarten; Vanathi Gopalakrishnan; Himanshu Grover; Shyam Visweswaran (AMIA, 2008)

Improving Peptide Identification via Validation with Intensity-based Modeling of Tandem Mass Spectra. - Himanshu Grover; Jonathan L. Lustgarten; Shyam Visweswaran; Vanathi Gopalakrishnan (BCBGC, 2008)

An Evaluation of Discretization Methods for Learning Rules from Biomedical Datasets. - Jonathan L. Lustgarten; Shyam Visweswaran; Himanshu Grover; Vanathi Gopalakrishnan (BIOCOMP, 2008)

Measuring Stability of Feature Selection in Biomedical Datasets. - Jonathan L. Lustgarten; Vanathi Gopalakrishnan; Shyam Visweswaran (AMIA, 2009)

Knowledge-based variable selection for learning rules from proteomic data. - Jonathan L. Lustgarten; Shyam Visweswaran; Robert P. Bowser; William R. Hogan; Vanathi Gopalakrishnan (BMC Bioinform., 2009)

Conditional Graphical Models for Protein Structural Motif Recognition. - Yan Liu 002; Jaime G. Carbonell; Vanathi Gopalakrishnan; Peter Weigele (J. Comput. Biol., 2009)

Bayesian rule learning for biomedical data mining. - Vanathi Gopalakrishnan; Jonathan L. Lustgarten; Shyam Visweswaran; Gregory F. Cooper (Bioinform., 2010)

Application of an efficient Bayesian discretization method to biomedical data. - Jonathan L. Lustgarten; Shyam Visweswaran; Vanathi Gopalakrishnan; Gregory F. Cooper (BMC Bioinform., 2011)

Transfer learning of classification rules for biomarker discovery and verification from molecular profiling studies. - Philip Ganchev; David Malehorn; William L. Bigbee; Vanathi Gopalakrishnan (J. Biomed. Informatics, 2011)

Efficient processing of models for large-scale shotgun proteomics data. - Himanshu Grover; Vanathi Gopalakrishnan (CollaborateCom, 2012)

Application of Bayesian Logistic Regression to Mining Biomedical Data. - Viji R. Avali; Gregory F. Cooper; Vanathi Gopalakrishnan (AMIA, 2014)

A novel framework to enhance scientific knowledge of cardiovascular MRI biomarkers and their application to pediatric cardiomyopathy classification. - Vanathi Gopalakrishnan; Prahlad G. Menon; Shobhit Madan (IWBBIO, 2014)

Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning framework. - Prahlad G. Menon; Lailonny Morris; Mara Staines; João A. C. Lima; Daniel C. Lee 002; Vanathi Gopalakrishnan (Image Processing, 2014)

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids. - Rick Jordan; Shyam Visweswaran; Vanathi Gopalakrishnan (J. Clin. Bioinform., 2014)

Quantitative clinical guidelines for imaging use in evaluation of pediatric cardiomyopathy. - Yuzhe Liu 001; Vanathi Gopalakrishnan; Shobhit Madan (BIBM, 2015)

Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression data. - Henry Ogoe; Shyam Visweswaran; Xinghua Lu 001; Vanathi Gopalakrishnan (BMC Bioinform., 2015)

Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations. - Mahbaneh Eshaghzadeh Torbati; Makedonka Mitreva; Vanathi Gopalakrishnan (Data, 2016)

An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data. - Yuzhe Liu 001; Vanathi Gopalakrishnan (Data, 2017)

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure. - Jonathan L. Lustgarten; Jeya Balaji Balasubramanian; Shyam Visweswaran; Vanathi Gopalakrishnan (Data, 2017)

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural Networks. - Rafael Ceschin; Alexandria Zahner; William Reynolds; Jenna Gaesser; Giulio Zuccoli; Cecilia W. Lo; Vanathi Gopalakrishnan; Ashok Panigrahy (NeuroImage, 2018)

A novel approach to modeling multifactorial diseases using Ensemble Bayesian Rule classifiers. - Jeya Balaji Balasubramanian; Rebecca D. Boes; Vanathi Gopalakrishnan (J. Biomed. Informatics, 2020)

Artificial Intelligence's Grand Challenges: Past, Present, and Future. - Ganesh Mani; Frank Chen; Steve Cross; Thomas Kalil; Vanathi Gopalakrishnan; Francesca Rossi 001; Ken Stanley (AI Mag., 2021)