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DeepDTAF: a deep learning method to predict protein-ligand binding affinity

Briefings in bioinformatics, 2021-09, Vol.22 (5)

2021

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BACPI: a bi-directional attention neural network for compound–protein interaction and binding affinity prediction

Bioinformatics, 2022-03, Vol.38 (7), p.1995-2002

2022

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Prediction of lncRNA-disease associations based on inductive matrix completion

Bioinformatics, 2018-10, Vol.34 (19), p.3357-3364

2018

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Computational drug repositioning based on multi-similarities bilinear matrix factorization

Briefings in bioinformatics, 2021-07, Vol.22 (4)

2021

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Biomedical data and computational models for drug repositioning: a comprehensive review

Briefings in bioinformatics, 2021-03, Vol.22 (2), p.1604-1619

2021

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DeepEP: a deep learning framework for identifying essential proteins

BMC bioinformatics, 2019-12, Vol.20 (Suppl 16), p.506-506, Article 506

2019

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Clinical big data and deep learning: Applications, challenges, and future outlooks

Big Data Mining and Analytics, 2019-12, Vol.2 (4), p.288-305

2019

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DeepFrag-k: a fragment-based deep learning approach for protein fold recognition

BMC bioinformatics, 2020-11, Vol.21 (Suppl 6), p.203-203, Article 203

2020

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A survey of matrix completion methods for recommendation systems

Big Data Mining and Analytics, 2018-12, Vol.1 (4), p.308-323

2018

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Overlap matrix completion for predicting drug-associated indications

PLoS computational biology, 2019-12, Vol.15 (12), p.e1007541-e1007541

2019

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A breakdown-free block conjugate gradient method

BIT, 2017-06, Vol.57 (2), p.379-403

2017

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scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data

Nature communications, 2024-08, Vol.15 (1), p.7561-20, Article 7561

2024

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HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation

Nature communications, 2024-07, Vol.15 (1), p.5573-14, Article 5573

2024

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Block Conjugate Gradient algorithms for least squares problems

Journal of computational and applied mathematics, 2017-06, Vol.317, p.203-217

2017

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A-RFP: An Adaptive Residue Flexibility Prediction Method Improving Protein-ligand Docking Based on Homologous Proteins

Current bioinformatics, 2024-12, Vol.19 (10), p.908-918

2024

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Identifying At-Risk Students for Early Interventions-A Time-Series Clustering Approach

IEEE transactions on emerging topics in computing, 2017-01, Vol.5 (1), p.45-55

2017

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Conformational sampling in template-free protein loop structure modeling: an overview

Computational and structural biotechnology journal, 2013-02, Vol.5 (6), p.e201302003-e201302003, Article e201302003

Li, Yaohang

2013

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Big data-enabled multiscale serviceability analysis for aging bridges

Digital communications and networks, 2016-08, Vol.2 (3), p.97-107

2016

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Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework

Communications biology, 2023-08, Vol.6 (1), p.870-870, Article 870

2023

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Building a Knowledge-Based Statistical Potential by Capturing High-Order Inter-residue Interactions and its Applications in Protein Secondary Structure Assessment

Journal of chemical information and modeling, 2013-02, Vol.53 (2), p.500-508

2013

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Drug repositioning based on bounded nuclear norm regularization

Bioinformatics, 2019-07, Vol.35 (14), p.i455-i463

2019

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Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy

Journal of chemical information and modeling, 2014-03, Vol.54 (3), p.992-1002

2014

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Sampling Multiple Scoring Functions Can Improve Protein Loop Structure Prediction Accuracy

Journal of chemical information and modeling, 2011-07, Vol.51 (7), p.1656-1666

2011

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Backbone Statistical Potential from Local Sequence-Structure Interactions in Protein Loops

The journal of physical chemistry. B, 2010-02, Vol.114 (5), p.1859-1869

2010

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A convolutional neural network and graph convolutional network-based method for predicting the classification of anatomical therapeutic chemicals

Bioinformatics (Oxford, England), 2021-09, Vol.37 (18), p.2841-2847

2021

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DeepDTAF: a deep learning method to predict protein-ligand binding affinity

BACPI: a bi-directional attention neural network for compound–protein interaction and binding affinity prediction

Prediction of lncRNA-disease associations based on inductive matrix completion

Computational drug repositioning based on multi-similarities bilinear matrix factorization

Biomedical data and computational models for drug repositioning: a comprehensive review

DeepEP: a deep learning framework for identifying essential proteins

Clinical big data and deep learning: Applications, challenges, and future outlooks

DeepFrag-k: a fragment-based deep learning approach for protein fold recognition

A survey of matrix completion methods for recommendation systems

Overlap matrix completion for predicting drug-associated indications

A breakdown-free block conjugate gradient method

scCAD: Cluster decomposition-based anomaly detection for rare cell identification in single-cell expression data

HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation

Block Conjugate Gradient algorithms for least squares problems

A-RFP: An Adaptive Residue Flexibility Prediction Method Improving Protein-ligand Docking Based on Homologous Proteins

Identifying At-Risk Students for Early Interventions-A Time-Series Clustering Approach

Conformational sampling in template-free protein loop structure modeling: an overview

Big data-enabled multiscale serviceability analysis for aging bridges

Identifying the serious clinical outcomes of adverse reactions to drugs by a multi-task deep learning framework

Building a Knowledge-Based Statistical Potential by Capturing High-Order Inter-residue Interactions and its Applications in Protein Secondary Structure Assessment

Drug repositioning based on bounded nuclear norm regularization

Context-Based Features Enhance Protein Secondary Structure Prediction Accuracy

Sampling Multiple Scoring Functions Can Improve Protein Loop Structure Prediction Accuracy

Backbone Statistical Potential from Local Sequence-Structure Interactions in Protein Loops

A convolutional neural network and graph convolutional network-based method for predicting the classification of anatomical therapeutic chemicals

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