Feature Extraction Approaches for Biological Sequences: A Comparative Study of Mathematical Models | bioRxiv
Deep learning models in genomics; are we there yet? - ScienceDirect
Frontiers | How Computation Is Helping Unravel the Dynamics of Morphogenesis
PDF) Recent Advances of Deep Learning in Bioinformatics and Computational Biology
Characterization and Identification of Lysine Succinylation Sites based on Deep Learning Method | Scientific Reports
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
PDF) Machine learning meets genome assembly
Frontiers | Artificial Intelligence for Cardiac Imaging-Genetics Research
Deep Learning for AI: turning the GPS on
Reinforced Adversarial Neural Computer for de Novo Molecular Design | Journal of Chemical Information and Modeling
gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning | Scientific Reports
Deep learning in bioinformatics | Briefings in Bioinformatics | Oxford Academic
Frontiers | Deep Learning for Predicting Complex Traits in Spring Wheat Breeding Program
A novel hybrid framework for metabolic pathways prediction based on the graph attention network | BMC Bioinformatics | Full Text
autoBioSeqpy: A Deep Learning Tool for the Classification of Biological Sequences | Journal of Chemical Information and Modeling
Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets | Molecular Pharmaceutics
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
Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data | Journal of Proteome Research
Improved sequence-based prediction of interaction sites in α-helical transmembrane proteins by deep learning - ScienceDirect
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
