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Predicting RNA-protein interactions using only sequence information

BMC bioinformatics, 2011-12, Vol.12 (1), p.489-489, Article 489

2011

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MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

Biomolecules (Basel, Switzerland), 2023-01, Vol.13 (1), p.121

2023

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Two-dimensional hybrid organic–inorganic perovskites as emergent ferroelectric materials

Journal of applied physics, 2020-08, Vol.128 (6)

2020

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In Silico Prediction of Linear B-Cell Epitopes on Proteins

Methods in molecular biology (Clifton, N.J.), 2017-01, Vol.1484, p.255

2017

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Machine learning in clinical care: Quo vadis?

Indian journal of ophthalmology, 2019-07, Vol.67 (7), p.985-986

Honavar, Vasant

2019

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A Proteomic Analysis of Maize Chloroplast Biogenesis

Plant physiology (Bethesda), 2004-02, Vol.134 (2), p.560-574

2004

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Connected in health: Place-to-place commuting networks and COVID-19 spillovers

Health & place, 2022-09, Vol.77, p.102891-102891, Article 102891

2022

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The Promise and Potential of Big Data: A Case for Discovery Informatics

The Review of policy research, 2014-07, Vol.31 (4), p.326-330

Honavar, Vasant G.

2014

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Partner‐specific prediction of RNA‐binding residues in proteins: A critical assessment

Proteins, structure, function, and bioinformatics, 2019-03, Vol.87 (3), p.198-211

2019

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Acceptability of Personal Sensing to Develop a Digital Biomarker of Stress-Related Injury Risk in Athletes: 2433 Board #269 June 1 9: 30 AM - 11: 00 AM

Medicine and science in sports and exercise, 2018-05, Vol.50 (5S Suppl 1), p.605-605

2018

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Personalized Sleep Parameters Estimation from Actigraphy: A Machine Learning Approach

Nature and science of sleep, 2019-12, Vol.11, p.387-399

2019

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Sequence-Based Prediction of RNA-Binding Residues in Proteins

Methods in molecular biology (Clifton, N.J.), 2017-01, Vol.1484, p.205

2017

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Corrigendum to “Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing” [Sleep Health 9 (2023) 596-610]

Sleep health, 2024-04, Vol.10 (2), p.255-260

2024

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Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing

Sleep health, 2023-10, Vol.9 (5), p.596-610

2023

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Characterization of the retinal proteome during rod photoreceptor genesis

BMC research notes, 2010-01, Vol.3 (1), p.25-25

2010

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Modular Ontologies – A Formal Investigation of Semantics and Expressivity

Lecture notes in computer science, 2006, p.616-631

2006

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Using a Seed-Network to Query Multiple Large-Scale Gene Expression Datasets from the Developing Retina in Order to Identify and Prioritize Experimental Targets

Bioinformatics and biology insights, 2008-01, Vol.2008 (2), p.BBI.S417-412

2008

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On the Semantics of Linking and Importing in Modular Ontologies

Lecture notes in computer science, 2006, p.72-86

2006

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A Proteomic Analysis of Maize Chloroplast Biogenesis1

Plant physiology (Bethesda), 2004-02, Vol.134 (2), p.560-574

2004

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PATENet: Pairwise Alignment of Time Evolving Networks

Machine Learning and Data Mining in Pattern Recognition, 2018, Vol.10934, p.85-98

2018

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Package-Based Description Logics – Preliminary Results

Lecture notes in computer science, 2006, p.967-969

2006

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Using a seed-network to query multiple large-scale gene expression datasets from the developing retina in order to identify and prioritize experimental targets

Bioinformatics and biology insights, 2008-02, Vol.2, p.401-412

2008

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Auto-steered Information-Decision Processes for Electric System Asset Management

Computational Science – ICCS 2006, 2006, p.440-447

2006

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A framework for semantic web services discovery

Proceedings of the 7th annual ACM international workshop on Web information and data management, 2005, p.45-50

2005

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Learning Classifiers from Semantically Heterogeneous Data

On the Move to Meaningful Internet Systems 2004: CoopIS, DOA, and ODBASE, p.963-980

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Predicting RNA-protein interactions using only sequence information

MetaScore: A Novel Machine-Learning-Based Approach to Improve Traditional Scoring Functions for Scoring Protein-Protein Docking Conformations

Two-dimensional hybrid organic–inorganic perovskites as emergent ferroelectric materials

In Silico Prediction of Linear B-Cell Epitopes on Proteins

Machine learning in clinical care: Quo vadis?

A Proteomic Analysis of Maize Chloroplast Biogenesis

Connected in health: Place-to-place commuting networks and COVID-19 spillovers

The Promise and Potential of Big Data: A Case for Discovery Informatics

Partner‐specific prediction of RNA‐binding residues in proteins: A critical assessment

Acceptability of Personal Sensing to Develop a Digital Biomarker of Stress-Related Injury Risk in Athletes: 2433 Board #269 June 1 9: 30 AM - 11: 00 AM

Personalized Sleep Parameters Estimation from Actigraphy: A Machine Learning Approach

Sequence-Based Prediction of RNA-Binding Residues in Proteins

Corrigendum to “Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing” [Sleep Health 9 (2023) 596-610]

Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing

Characterization of the retinal proteome during rod photoreceptor genesis

Modular Ontologies – A Formal Investigation of Semantics and Expressivity

Using a Seed-Network to Query Multiple Large-Scale Gene Expression Datasets from the Developing Retina in Order to Identify and Prioritize Experimental Targets

On the Semantics of Linking and Importing in Modular Ontologies

A Proteomic Analysis of Maize Chloroplast Biogenesis1

PATENet: Pairwise Alignment of Time Evolving Networks

Package-Based Description Logics – Preliminary Results

Using a seed-network to query multiple large-scale gene expression datasets from the developing retina in order to identify and prioritize experimental targets

Auto-steered Information-Decision Processes for Electric System Asset Management

A framework for semantic web services discovery

Learning Classifiers from Semantically Heterogeneous Data

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