Frontiers | Recent Advances of Deep Learning in Bioinformatics and Computational Biology
Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data | Journal of Proteome Research
Characterization and Identification of Lysine Succinylation Sites based on Deep Learning Method | Scientific Reports
Deep Learning for AI: turning the GPS on
Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning - ScienceDirect
Deep Neural Network-Assisted Drug Recommendation Systems for Identifying Potential Drug–Target Interactions | ACS Omega
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
Predicting Drug-Induced Liver Injury Using Convolutional Neural Network and Molecular Fingerprint-Embedded Features | ACS Omega
autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences | Journal of Chemical Information and Modeling
gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning | Scientific Reports
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife
Frontiers | Comparison of a Machine Learning Method and Various Equations for Estimating Low-Density Lipoprotein Cholesterol in Korean Populations
Frontiers | Deep Learning-Based Protein Features Predict Overall Survival and Chemotherapy Benefit in Gastric Cancer
Deep learning in bioinformatics | Briefings in Bioinformatics | Oxford Academic
PDF) Machine learning meets genome assembly
PARROT is a flexible recurrent neural network framework for analysis of large protein datasets | eLife
Deep learning models in genomics; are we there yet? - ScienceDirect
Frontiers | Graph Neural Networks and Their Current Applications in Bioinformatics
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 | How Computation Is Helping Unravel the Dynamics of Morphogenesis
A novel hybrid framework for metabolic pathways prediction based on the graph attention network | BMC Bioinformatics | Full Text
Frontiers | Artificial Intelligence for Cardiac Imaging-Genetics Research
Full article: Machine learning for epigenetics and future medical applications
The language of proteins: NLP, machine learning & protein sequences - ScienceDirect
