A novel hybrid framework for metabolic pathways prediction based on the graph attention network | BMC Bioinformatics | Full Text
Characterization and Identification of Lysine Succinylation Sites based on Deep Learning Method | Scientific Reports
Deep learning models in genomics; are we there yet? - ScienceDirect
Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning - ScienceDirect
Frontiers | Applications of machine learning in metabolomics: Disease modeling and classification
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife
Deep Neural Network-Assisted Drug Recommendation Systems for Identifying Potential Drug–Target Interactions | ACS Omega
Reinforced Adversarial Neural Computer for de Novo Molecular Design | Journal of Chemical Information and Modeling
Deep Learning for AI: turning the GPS on
Deep learning in bioinformatics | Briefings in Bioinformatics | Oxford Academic
Frontiers | Graph Neural Networks and Their Current Applications in Bioinformatics
Frontiers | How Computation Is Helping Unravel the Dynamics of Morphogenesis
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife
Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv
Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning - ScienceDirect
gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning | Scientific Reports
autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences | Journal of Chemical Information and Modeling
Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features | ACS Omega
Frontiers | Recent Advances of Deep Learning in Bioinformatics and Computational Biology
PDF) Machine learning meets genome assembly
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
Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets | Molecular Pharmaceutics
Frontiers | Comparison of a Machine Learning Method and Various Equations for Estimating Low-Density Lipoprotein Cholesterol in Korean Populations
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife
