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Predicting drug-target interactions using restricted Boltzmann machines

Bioinformatics, 2013-07, Vol.29 (13), p.i126-i134

2013

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NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug–target interactions

Bioinformatics, 2019-01, Vol.35 (1), p.104-111

2019

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A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

Nature communications, 2017-09, Vol.8 (1), p.573-13, Article 573

2017

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Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach

IEEE/ACM transactions on computational biology and bioinformatics, 2015-07, Vol.12 (4), p.928-937

2015

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A deep-learning framework for multi-level peptide-protein interaction prediction

Nature communications, 2021-09, Vol.12 (1), p.5465-10, Article 5465

2021

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TITER: predicting translation initiation sites by deep learning

Bioinformatics (Oxford, England), 2017-07, Vol.33 (14), p.i234-i242

2017

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MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities

Cell systems, 2020-04, Vol.10 (4), p.308-322.e11

2020

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Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes

Nature communications, 2019-05, Vol.10 (1), p.2049-2049, Article 2049

2019

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DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM

Journal of structural biology, 2016-09, Vol.195 (3), p.325-336

2016

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Allelic reprogramming of 3D chromatin architecture during early mammalian development

Nature (London), 2017-07, Vol.547 (7662), p.232-235

2017

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A knowledge-guided pre-training framework for improving molecular representation learning

Nature communications, 2023-11, Vol.14 (1), p.7568-7568, Article 7568

2023

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DeepShape: estimating isoform-level ribosome abundance and distribution with Ribo-seq data

BMC bioinformatics, 2019-12, Vol.20 (Suppl 24), p.678-678, Article 678

2019

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An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

Signal transduction and targeted therapy, 2021-04, Vol.6 (1), p.165-165, Article 165

2021

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Full-length ribosome density prediction by a multi-input and multi-output model

PLoS computational biology, 2021-03, Vol.17 (3), p.e1008842-e1008842

2021

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Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Nature communications, 2023-12, Vol.14 (1), p.8459-8459, Article 8459

2023

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FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome

Nucleic acids research, 2018-01, Vol.46 (2), p.e11

2018

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Understanding the phase separation characteristics of nucleocapsid protein provides a new therapeutic opportunity against SARS-CoV-2

Protein & cell, 2021-09, Vol.12 (9), p.734-740

2021

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DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening

Genomics, proteomics & bioinformatics, 2019-10, Vol.17 (5), p.478-495

2019

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Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning

Cell systems, 2017-09, Vol.5 (3), p.212-220.e6

2017

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EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction

Frontiers in pharmacology, 2020-02, Vol.11, p.112-112

2020

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Genomic basis of recombination suppression in the hybrid between Caenorhabditis briggsae and C. nigoni

Nucleic acids research, 2018-02, Vol.46 (3), p.1295

2018

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Characterizing RNA Pseudouridylation by Convolutional Neural Networks

Genomics, proteomics & bioinformatics, 2021-10, Vol.19 (5), p.815-833

2021

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Improving molecular property prediction through a task similarity enhanced transfer learning strategy

iScience, 2022-10, Vol.25 (10), p.105231-105231, Article 105231

2022

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Author Correction: Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Nature communications, 2024-02, Vol.15 (1), p.1323-1323

2024

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Network-based screening identifies sitagliptin as an antitumor drug targeting dendritic cells

Journal for immunotherapy of cancer, 2024-03, Vol.12 (3), p.e008254

2024

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Predicting drug-target interactions using restricted Boltzmann machines

NeoDTI: neural integration of neighbor information from a heterogeneous network for discovering new drug–target interactions

A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach

A deep-learning framework for multi-level peptide-protein interaction prediction

TITER: predicting translation initiation sites by deep learning

MONN: A Multi-objective Neural Network for Predicting Compound-Protein Interactions and Affinities

Integrating Hi-C and FISH data for modeling of the 3D organization of chromosomes

DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM

Allelic reprogramming of 3D chromatin architecture during early mammalian development

A knowledge-guided pre-training framework for improving molecular representation learning

DeepShape: estimating isoform-level ribosome abundance and distribution with Ribo-seq data

An integrative drug repositioning framework discovered a potential therapeutic agent targeting COVID-19

Full-length ribosome density prediction by a multi-input and multi-output model

Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

FreePSI: an alignment-free approach to estimating exon-inclusion ratios without a reference transcriptome

Understanding the phase separation characteristics of nucleocapsid protein provides a new therapeutic opportunity against SARS-CoV-2

DeepCPI: A Deep Learning-based Framework for Large-scale in silico Drug Screening

Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning

EXP2SL: A Machine Learning Framework for Cell-Line-Specific Synthetic Lethality Prediction

Genomic basis of recombination suppression in the hybrid between Caenorhabditis briggsae and C. nigoni

Characterizing RNA Pseudouridylation by Convolutional Neural Networks

Improving molecular property prediction through a task similarity enhanced transfer learning strategy

Author Correction: Deciphering driver regulators of cell fate decisions from single-cell transcriptomics data with CEFCON

Network-based screening identifies sitagliptin as an antitumor drug targeting dendritic cells

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