Vanathi Gopalakrishnan - researchr alias

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Viewing Publication 1 - 35 from 35

2021

Artificial Intelligence's Grand Challenges: Past, Present, and FutureGanesh Mani, Frank Chen, Steve Cross, Thomas Kalil, Vanathi Gopalakrishnan, Francesca Rossi, Ken Stanley. aim, 42(1):61-75, 2021. [doi]

2020

A novel approach to modeling multifactorial diseases using Ensemble Bayesian Rule classifiersJeya Balaji Balasubramanian, Rebecca D. Boes, Vanathi Gopalakrishnan. jbi, 107:103455, 2020. [doi]

2018

A computational framework for the detection of subcortical brain dysmaturation in neonatal MRI using 3D Convolutional Neural NetworksRafael Ceschin, Alexandria Zahner, William Reynolds, Jenna Gaesser, Giulio Zuccoli, Cecilia W. Lo, Vanathi Gopalakrishnan, Ashok Panigrahy. neuroimage, 178:183-197, 2018. [doi]

2017

An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging DataYuzhe Liu, Vanathi Gopalakrishnan. data, 2(1):8, 2017. [doi]

Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local StructureJonathan L. Lustgarten, Jeya Balaji Balasubramanian, Shyam Visweswaran, Vanathi Gopalakrishnan. data, 2(1):5, 2017. [doi]

2016

Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global PopulationsMahbaneh Eshaghzadeh Torbati, Makedonka Mitreva, Vanathi Gopalakrishnan. data, 1(3):19, 2016. [doi]

2015

Quantitative clinical guidelines for imaging use in evaluation of pediatric cardiomyopathyYuzhe Liu, Vanathi Gopalakrishnan, Shobhit Madan. bibm 2015: 1572-1578 [doi]

Knowledge transfer via classification rules using functional mapping for integrative modeling of gene expression dataHenry Ogoe, Shyam Visweswaran, Xinghua Lu, Vanathi Gopalakrishnan. bmcbi, 16:226, 2015. [doi]

2014

Application of Bayesian Logistic Regression to Mining Biomedical DataViji R. Avali, Gregory F. Cooper, Vanathi Gopalakrishnan. amia 2014: [doi]

A novel framework to enhance scientific knowledge of cardiovascular MRI biomarkers and their application to pediatric cardiomyopathy classificationVanathi Gopalakrishnan, Prahlad G. Menon, Shobhit Madan. iwbbio 2014: 798-809 [doi]

Semi-automated literature mining to identify putative biomarkers of disease from multiple biofluidsRick Jordan, Shyam Visweswaran, Vanathi Gopalakrishnan. jclinbioinf, 4:13, 2014. [doi]

Novel MRI-derived quantitative biomarker for cardiac function applied to classifying ischemic cardiomyopathy within a Bayesian rule learning frameworkPrahlad G. Menon, Lailonny Morris, Mara Staines, João A. C. Lima, Daniel C. Lee 0002, Vanathi Gopalakrishnan. miip 2014: [doi]

2012

Efficient processing of models for large-scale shotgun proteomics dataHimanshu Grover, Vanathi Gopalakrishnan. colcom 2012: 591-596 [doi]

2011

Transfer learning of classification rules for biomarker discovery and verification from molecular profiling studiesPhilip Ganchev, David Malehorn, William L. Bigbee, Vanathi Gopalakrishnan. jbi, 44(Supplement-1), 2011. [doi]

Application of an efficient Bayesian discretization method to biomedical dataJonathan L. Lustgarten, Shyam Visweswaran, Vanathi Gopalakrishnan, Gregory F. Cooper. bmcbi, 12:309, 2011. [doi]

2010

Bayesian rule learning for biomedical data miningVanathi Gopalakrishnan, Jonathan L. Lustgarten, Shyam Visweswaran, Gregory F. Cooper. bioinformatics, 26(5):668-675, 2010. [doi]

2009

2008

Improving Peptide Identification via Validation with Intensity-based Modeling of Tandem Mass SpectraHimanshu Grover, Jonathan L. Lustgarten, Shyam Visweswaran, Vanathi Gopalakrishnan. bcbgc 2008: 56-63

Improving Classification Performance with Discretization on Biomedical DatasetsJonathan L. Lustgarten, Vanathi Gopalakrishnan, Himanshu Grover, Shyam Visweswaran. amia 2008: [doi]

An Evaluation of Discretization Methods for Learning Rules from Biomedical DatasetsJonathan L. Lustgarten, Shyam Visweswaran, Himanshu Grover, Vanathi Gopalakrishnan. psb 2008: 527-532

2007

Protein Quaternary Fold Recognition Using Conditional Graphical ModelsYan Liu, Jaime G. Carbonell, Vanathi Gopalakrishnan, Peter Weigele. IJCAI 2007: 937-945 [doi]

2006

2005

Segmentation Conditional Random Fields (SCRFs): A New Approach for Protein Fold RecognitionYan Liu, Jaime G. Carbonell, Peter Weigele, Vanathi Gopalakrishnan. recomb 2005: 408-422 [doi]

2004

2000

Intelligent Aids for Parallel Experiment Planning and Macromolecular CrystallizationVanathi Gopalakrishnan, Bruce G. Buchanan, John M. Rosenberg. ismb 2000: 171-182

1998

Representing and Learning Temporal Relationships among Experimental VariablesVanathi Gopalakrishnan, Bruce G. Buchanan. time 1998: 148-155 [doi]

1996

Inducing Design Biases that Characterize Successful Experimentation in Weak-Theory Domains: TIPSVanathi Gopalakrishnan. AAAI 1996: 1391

1994

The Crystallographer s AssistantVanathi Gopalakrishnan, Daniel N. Hennessy, Bruce G. Buchanan, Devika Subramanian. AAAI 1994: 1451

Induction of Rules for Biological Macromolecular CrystallizationDaniel N. Hennessy, Vanathi Gopalakrishnan, Bruce G. Buchanan, John M. Rosenberg, Devika Subramanian. ismb 1994: 179-187

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