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PARROT is a flexible recurrent neural network framework for analysis of  large protein datasets | eLife
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife

Characterization and Identification of Lysine Succinylation Sites based on  Deep Learning Method | Scientific Reports
Characterization and Identification of Lysine Succinylation Sites based on Deep Learning Method | Scientific Reports

Integrated omics: tools, advances and future approaches in: Journal of  Molecular Endocrinology Volume 62 Issue 1 (2019)
Integrated omics: tools, advances and future approaches in: Journal of Molecular Endocrinology Volume 62 Issue 1 (2019)

Improving Clinical Prediction of Later Occurrence of Breast Cancer  Metastasis Using Deep Learning and Machine Learning with Grid
Improving Clinical Prediction of Later Occurrence of Breast Cancer Metastasis Using Deep Learning and Machine Learning with Grid

Data Integration Using Advances in Machine Learning in Drug Discovery and  Molecular Biology | SpringerLink
Data Integration Using Advances in Machine Learning in Drug Discovery and Molecular Biology | SpringerLink

Multiset sparse partial least squares path modeling for high dimensional  omics data analysis | BMC Bioinformatics | Full Text
Multiset sparse partial least squares path modeling for high dimensional omics data analysis | BMC Bioinformatics | Full Text

Improving Clinical Prediction of Later Occurrence of Breast Cancer  Metastasis Using Deep Learning and Machine Learning with Grid
Improving Clinical Prediction of Later Occurrence of Breast Cancer Metastasis Using Deep Learning and Machine Learning with Grid

Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and  Molecular Fingerprint-Embedded Features | ACS Omega
Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features | ACS Omega

PDF) Recent Advances of Deep Learning in Bioinformatics and Computational  Biology
PDF) Recent Advances of Deep Learning in Bioinformatics and Computational Biology

Opportunities and obstacles for deep learning in biology and medicine: 2019  update
Opportunities and obstacles for deep learning in biology and medicine: 2019 update

Improved sequence-based prediction of interaction sites in α-helical  transmembrane proteins by deep learning - ScienceDirect
Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning - ScienceDirect

autoBioSeqpy: A Deep Learning Tool for the Classification of Biological  Sequences | Journal of Chemical Information and Modeling
autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences | Journal of Chemical Information and Modeling

A Transdisciplinary Review of Deep Learning Research and Its Relevance for  Water Resources Scientists - Shen - 2018 - Water Resources Research - Wiley  Online Library
A Transdisciplinary Review of Deep Learning Research and Its Relevance for Water Resources Scientists - Shen - 2018 - Water Resources Research - Wiley Online Library

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer  Metabolomics Data | Journal of Proteome Research
Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data | Journal of Proteome Research

Frontiers | Recent Advances of Deep Learning in Bioinformatics and  Computational Biology
Frontiers | Recent Advances of Deep Learning in Bioinformatics and Computational Biology

Convolutional neural networks (CNNs): concepts and applications in  pharmacogenomics | SpringerLink
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics | SpringerLink

gammaBOriS: Identification and Taxonomic Classification of Origins of  Replication in Gammaproteobacteria using Motif-based Machine Learning |  Scientific Reports
gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning | Scientific Reports

PDF) Machine learning meets genome assembly
PDF) Machine learning meets genome assembly

Frontiers | A Brief Review on Deep Learning Applications in Genomic Studies
Frontiers | A Brief Review on Deep Learning Applications in Genomic Studies

Frontiers | Graph Neural Networks and Their Current Applications in  Bioinformatics
Frontiers | Graph Neural Networks and Their Current Applications in Bioinformatics

Feature Extraction Approaches for Biological Sequences: A Comparative Study  of Mathematical Models | bioRxiv
Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv

PARROT is a flexible recurrent neural network framework for analysis of  large protein datasets | eLife
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife

Frontiers | Deep Learning-Based Structure-Activity Relationship Modeling  for Multi-Category Toxicity Classification: A Case Study of 10K Tox21  Chemicals With High-Throughput Cell-Based Androgen Receptor Bioassay Data
Frontiers | Deep Learning-Based Structure-Activity Relationship Modeling for Multi-Category Toxicity Classification: A Case Study of 10K Tox21 Chemicals With High-Throughput Cell-Based Androgen Receptor Bioassay Data