Subramani Mani

According to our database, Subramani Mani authored at least 36 papers between 1997 and 2017.

Collaborative distances:

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

2017

Pharos: Collating protein information to shed light on the druggable genome.

Dac-Trung Nguyen, Stephen L. Mathias, Cristian Bologa, Søren Brunak, Nicolas F. Fernandez, Anna Gaulton, Anne Hersey, Jayme Holmes, Lars Juhl Jensen, Anneli Karlsson, Guixia Liu, Avi Ma'ayan, Geetha Mandava, Subramani Mani, Saurabh Mehta, John P. Overington, Juhee Patel, Andrew D. Rouillard, Stephan C. Schürer, Timothy Sheils, Anton Simeonov, Larry A. Sklar, Noel Southall, Oleg Ursu, Dusica Vidovic, Anna Waller, Jeremy J. Yang, Ajit Jadhav, Tudor I. Oprea, Rajarshi Guha

Nucleic Acids Res., 2017

Protein biomarker druggability profiling.

Subramani Mani, Daniel Cannon, Robin Ohls, Tudor I. Oprea, Stephen L. Mathias, Karri Ballard, Oleg Ursu, Cristian Bologa

J. Biomed. Informatics, 2017

Formalizing drug indications on the road to therapeutic intent.

Stuart J. Nelson, Tudor I. Oprea, Oleg Ursu, Cristian Bologa, Amrapali Zaveri, Jayme Holmes, Jeremy J. Yang, Stephen L. Mathias, Subramani Mani, Mark S. Tuttle, Michel Dumontier

J. Am. Medical Informatics Assoc., 2017

TIN-X: target importance and novelty explorer.

Daniel Cannon, Jeremy J. Yang, Stephen L. Mathias, Oleg Ursu, Subramani Mani, Anna Waller, Stephan C. Schürer, Lars Juhl Jensen, Larry A. Sklar, Cristian Bologa, Tudor I. Oprea

Bioinform., 2017

2016

Protein Biomarker Discovery and Ranking for Early Detection of Necrotizing Enterocolitis in Neonates.

Subramani Mani, Daniel Cannon, Karri Ballard, Robin Ohls

Proceedings of the AMIA 2016, 2016

2015

Protein Drug Target Prioritization for Illumination.

Subramani Mani, Daniel Cannon, Tudor I. Oprea, Stephen L. Mathias, Oleg Ursu, Cristian Bologa

Proceedings of the AMIA 2015, 2015

2014

Medical decision support using machine learning for early detection of late-onset neonatal sepsis.

Subramani Mani, Asli Ozdas, Constantin F. Aliferis, Huseyin Atakan Varol, Qingxia Chen, Randy J. Carnevale, Yukun Chen, Joann Romano-Keeler, Hui Nian, Jörn-Hendrik Weitkamp

J. Am. Medical Informatics Assoc., 2014

Genomic dark matter, druggability and misunderstood targets.

Subramani Mani, Joshua Swamidass, Noel Southall, Tudor I. Oprea

Proceedings of the AMIA 2014, 2014

2013

Research and applications: Machine learning for predicting the response of breast cancer to neoadjuvant chemotherapy.

Subramani Mani, Yukun Chen, Xia Li, Lori R. Arlinghaus, A. Bapsi Chakravarthy, Vandana G. Abramson, Sandeep R. Bhave, Mia A. Levy, Hua Xu, Thomas E. Yankeelov

J. Am. Medical Informatics Assoc., 2013

2012

Applying active learning to assertion classification of concepts in clinical text.

Yukun Chen, Subramani Mani, Hua Xu

J. Biomed. Informatics, 2012

Type 2 Diabetes Risk Forecasting from EMR Data using Machine Learning.

Subramani Mani, Yukun Chen, Tom Elasy, Warren Clayton, Joshua C. Denny

Proceedings of the AMIA 2012, 2012

2011

Active Learning for Unbalanced Data in the Challenge with Multiple Models and Biasing.

Yukun Chen, Subramani Mani

Proceedings of the Active Learning and Experimental Design workshop, 2011

A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries.

Min Jiang, Yukun Chen, Mei Liu, S. Trent Rosenbloom, Subramani Mani, Joshua C. Denny, Hua Xu

J. Am. Medical Informatics Assoc., 2011

2010

Bayesian Algorithms for Causal Data Mining.

Subramani Mani, Constantin F. Aliferis, Alexander R. Statnikov

Proceedings of the Causality: Objectives and Assessment (NIPS 2008 Workshop), 2010

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part II: Analysis and Extensions.

Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos

J. Mach. Learn. Res., 2010

Local Causal and Markov Blanket Induction for Causal Discovery and Feature Selection for Classification Part I: Algorithms and Empirical Evaluation.

Constantin F. Aliferis, Alexander R. Statnikov, Ioannis Tsamardinos, Subramani Mani, Xenofon D. Koutsoukos

J. Mach. Learn. Res., 2010

Letter: Note on Friedman's 'fundamental theorem of biomedical informatics'.

Subramani Mani

J. Am. Medical Informatics Assoc., 2010

Identifying potential drugs that induce QT prolongation using electronic medical records.

Mei Liu, Joshua C. Denny, Subramani Mani, Yukun Chen, Yong Hu, Hua Xu

BMC Bioinform., 2010

2009

Early Prediction of Reading Disability using Machine Learning.

Huseyin Atakan Varol, Subramani Mani, Donald L. Compton, Lynn S. Fuchs, Douglas Fuchs

Proceedings of the AMIA 2009, 2009

2007

Learning Causal and Predictive Clinical Practice Guidelines from Data.

Subramani Mani, Constantin F. Aliferis, Shanthi Krishnaswami, Theodore Kotchen

Proceedings of the MEDINFO 2007 - Proceedings of the 12th World Congress on Health (Medical) Informatics, 2007

A Causal Modeling Framework for Generating Clinical Practice Guidelines from Data.

Subramani Mani, Constantin F. Aliferis

Proceedings of the Artificial Intelligence in Medicine, 2007

2006

A Theoretical Study of Y Structures for Causal Discovery.

Subramani Mani, Gregory F. Cooper, Peter Spirtes

Proceedings of the UAI '06, 2006

2005

Building Bayesian Network Models in Medicine: The MENTOR Experience.

Subramani Mani, Marco Valtorta, Suzanne McDermott

Appl. Intell., 2005

2004

Causal Discovery Using A Bayesian Local Causal Discovery Algorithm.

Subramani Mani, Gregory F. Cooper

Proceedings of the MEDINFO 2004, 2004

2001

A Simulation Study of Three Related Causal Data Mining Algorithms.

Subramani Mani, Gregory F. Cooper

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000

Causal discovery from medical textual data.

Subramani Mani, Gregory F. Cooper

Proceedings of the AMIA 2000, 2000

1999

Two-Stage Machine Learning model for guideline development.

Subramani Mani, William Rodman Shankle, Malcolm B. Dick, Michael J. Pazzani

Artif. Intell. Medicine, 1999

A study in causal discovery from population-based infant birth and death records.

Subramani Mani, Gregory F. Cooper

Proceedings of the AMIA 1999, 1999

Refinement of Neuro-psychological Tests for Dementia Screening in a Cross Cultural Population Using Machine Learning.

Subramani Mani, Malcolm B. Dick, Michael J. Pazzani, Evelyn L. Teng, Daniel Kempler, I. Maribell Taussig

Proceedings of the Artificial Intelligence in Medicine. Joint European Conference on Artificial Intelligence in Medicine and Medical Decision Making, 1999

Causal Discovery from Population-Based Infant Birth and Death Records.

Subramani Mani, Gregory F. Cooper

Proceedings of the Sixteenth National Conference on Artificial Intelligence and Eleventh Conference on Innovative Applications of Artificial Intelligence, 1999

1998

Simple Models for Estimating Dementia Severity Using Machine Learning.

William Rodman Shankle, Subramani Mani, Malcolm B. Dick, Michael J. Pazzani

Proceedings of the MEDINFO '98, 1998

Guideline generation from data by induction of decision tables using a Bayesian network framework.

Subramani Mani, Michael J. Pazzani

Proceedings of the AMIA 1998, 1998

1997

Beyond Concise and Colorful: Learning Intelligible Rules.

Michael J. Pazzani, Subramani Mani, William Rodman Shankle

Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), 1997

Differential Diagnosis of Dementia: A Knowledge Discovery and Data Mining (KDD) Approach.

Subramani Mani, William Rodman Shankle, Michael J. Pazzani, Padhraic Smyth, Malcolm B. Dick

Proceedings of the AMIA 1997, 1997

Detecting Very Early Stages of Dementia from Normal Aging with Machine Learning Methods.

William Rodman Shankle, Subramani Mani, Michael J. Pazzani, Padhraic Smyth

Proceedings of the Artificial Intelligence Medicine, 1997

Knowledge Discovery from a Breast Cancer Database.

Subramani Mani, Michael J. Pazzani, John West

Proceedings of the Artificial Intelligence Medicine, 1997