Vanathi Gopalakrishnan

According to our database, Vanathi Gopalakrishnan authored at least 35 papers between 1994 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

Artificial Intelligence's Grand Challenges: Past, Present, and Future.

Ganesh Mani, Frank Chen, Steve Cross, Thomas Kalil, Vanathi Gopalakrishnan, Francesca Rossi, Ken Stanley

AI Mag., 2021

2020

A novel approach to modeling multifactorial diseases using Ensemble Bayesian Rule classifiers.

Jeya Balaji Balasubramanian, Rebecca D. Boes, Vanathi Gopalakrishnan

J. Biomed. Informatics, 2020

2018

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

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

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

Yuzhe Liu, Vanathi Gopalakrishnan

Data, 2017

2016

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

2015

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

Henry Ogoe, Shyam Visweswaran, Xinghua Lu, Vanathi Gopalakrishnan

BMC Bioinform., 2015

Quantitative clinical guidelines for imaging use in evaluation of pediatric cardiomyopathy.

Yuzhe Liu, Vanathi Gopalakrishnan, Shobhit Madan

Proceedings of the 2015 IEEE International Conference on Bioinformatics and Biomedicine, 2015

2014

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluids.

Rick Jordan, Shyam Visweswaran, Vanathi Gopalakrishnan

J. Clin. Bioinform., 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, Vanathi Gopalakrishnan

Proceedings of the Medical Imaging 2014: Image Processing, 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

Proceedings of the International Work-Conference on Bioinformatics and Biomedical Engineering, 2014

Application of Bayesian Logistic Regression to Mining Biomedical Data.

Viji R. Avali, Gregory F. Cooper, Vanathi Gopalakrishnan

Proceedings of the AMIA 2014, 2014

2012

Efficient processing of models for large-scale shotgun proteomics data.

Himanshu Grover, Vanathi Gopalakrishnan

Proceedings of the 8th International Conference on Collaborative Computing: Networking, 2012

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

Application of an efficient Bayesian discretization method to biomedical data.

Jonathan L. Lustgarten, Shyam Visweswaran, Vanathi Gopalakrishnan, Gregory F. Cooper

BMC Bioinform., 2011

2010

Bayesian rule learning for biomedical data mining.

Vanathi Gopalakrishnan, Jonathan L. Lustgarten, Shyam Visweswaran, Gregory F. Cooper

Bioinform., 2010

2009

Conditional Graphical Models for Protein Structural Motif Recognition.

Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele

J. Comput. Biol., 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

Measuring Stability of Feature Selection in Biomedical Datasets.

Jonathan L. Lustgarten, Vanathi Gopalakrishnan, Shyam Visweswaran

Proceedings of the AMIA 2009, 2009

2008

An Evaluation of Discretization Methods for Learning Rules from Biomedical Datasets.

Jonathan L. Lustgarten, Shyam Visweswaran, Himanshu Grover, Vanathi Gopalakrishnan

Proceedings of the International Conference on Bioinformatics & Computational Biology, 2008

Improving Peptide Identification via Validation with Intensity-based Modeling of Tandem Mass Spectra.

Himanshu Grover, Jonathan L. Lustgarten, Shyam Visweswaran, Vanathi Gopalakrishnan

Proceedings of the International Conference on Bioinformatics, 2008

Improving Classification Performance with Discretization on Biomedical Datasets.

Jonathan L. Lustgarten, Vanathi Gopalakrishnan, Himanshu Grover, Shyam Visweswaran

Proceedings of the AMIA 2008, 2008

2007

Protein Quaternary Fold Recognition Using Conditional Graphical Models.

Yan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele

Proceedings of the IJCAI 2007, 2007

2006

Protein Fold Recognition Using Segmentation Conditional Random Fields (SCRFs).

Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan

J. Comput. Biol., 2006

Rule Learning for Disease-Specific Biomarker Discovery from Clinical Proteomic Mass Spectra.

Vanathi Gopalakrishnan, Philip Ganchev, Srikanth Ranganathan, Robert P. Bowser

Proceedings of the Data Mining for Biomedical Applications, PAKDD 2006 Workshop, 2006

Segmentation of fMRI Data by Maximization of Region Contrast.

Pinaki S. Mitra, Vanathi Gopalakrishnan, Rebecca L. McNamee

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2006

2005

Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold Recognition.

Yan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan

Proceedings of the Research in Computational Molecular Biology, 2005

2004

Automatic annotation of protein motif function with Gene Ontology terms.

Xinghua Lu, Chengxiang Zhai, Vanathi Gopalakrishnan, Bruce G. Buchanan

BMC Bioinform., 2004

Comparison of probabilistic combination methods for protein secondary structure prediction.

Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan

Bioinform., 2004

Context sensitive vocabulary and its application in protein secondary structure prediction.

Yan Liu, Jaime G. Carbonell, Judith Klein-Seetharaman, Vanathi Gopalakrishnan

Proceedings of the SIGIR 2004: Proceedings of the 27th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2004

2000

Intelligent Aids for Parallel Experiment Planning and Macromolecular Crystallization.

Vanathi Gopalakrishnan, Bruce G. Buchanan, John M. Rosenberg

Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 2000

1998

Representing and Learning Temporal Relationships among Experimental Variables.

Vanathi Gopalakrishnan, Bruce G. Buchanan

Proceedings of the 5th Workshop on Temporal Representation and Reasoning, 1998

1996

Inducing Design Biases that Characterize Successful Experimentation in Weak-Theory Domains: TIPS.

Vanathi Gopalakrishnan

Proceedings of the Thirteenth National Conference on Artificial Intelligence and Eighth Innovative Applications of Artificial Intelligence Conference, 1996

1994

Induction of Rules for Biological Macromolecular Crystallization.

Daniel N. Hennessy, Vanathi Gopalakrishnan, Bruce G. Buchanan, John M. Rosenberg, Devika Subramanian

Proceedings of the Second International Conference on Intelligent Systems for Molecular Biology, 1994

The Crystallographer's Assistant.

Vanathi Gopalakrishnan, Daniel N. Hennessy, Bruce G. Buchanan, Devika Subramanian

Proceedings of the 12th National Conference on Artificial Intelligence, Seattle, WA, USA, July 31, 1994