Recent advances in deep learning for protein-protein interaction analysis: A comprehensive review
M Lee - Molecules, 2023 - mdpi.com
Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative
imprint across multiple disciplines. Within computational biology, it is expediting progress in …
imprint across multiple disciplines. Within computational biology, it is expediting progress in …
Genomics enters the deep learning era
E Routhier, J Mozziconacci - PeerJ, 2022 - peerj.com
The tremendous amount of biological sequence data available, combined with the recent
methodological breakthrough in deep learning in domains such as computer vision or …
methodological breakthrough in deep learning in domains such as computer vision or …
Functional annotation of enzyme-encoding genes using deep learning with transformer layers
Functional annotation of open reading frames in microbial genomes remains substantially
incomplete. Enzymes constitute the most prevalent functional gene class in microbial …
incomplete. Enzymes constitute the most prevalent functional gene class in microbial …
Deciphering the impact of genetic variation on human polyadenylation using APARENT2
Background 3′-end processing by cleavage and polyadenylation is an important and finely
tuned regulatory process during mRNA maturation. Numerous genetic variants are known to …
tuned regulatory process during mRNA maturation. Numerous genetic variants are known to …
Interpreting cis-regulatory interactions from large-scale deep neural networks
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene
expression has introduced challenges in their evaluation and interpretation. Current …
expression has introduced challenges in their evaluation and interpretation. Current …
Interpretable perturbator for variable selection in near-infrared spectral analysis
C Duan, X Liu, W Cai, X Shao - Journal of Chemical Information …, 2023 - ACS Publications
A perturbator was developed for variable selection in near-infrared (NIR) spectral analysis
based on the perturbation strategy in deep learning for develo** interpretation methods. A …
based on the perturbation strategy in deep learning for develo** interpretation methods. A …
Application of artificial intelligence tools in wastewater and waste gas treatment systems: Recent advances and prospects
The non-linear complex relationships among the process variables in wastewater and waste
gas treatment systems possess a significant challenge for real-time systems modelling. Data …
gas treatment systems possess a significant challenge for real-time systems modelling. Data …
Decoding biology with massively parallel reporter assays and machine learning
Massively parallel reporter assays (MPRAs) are powerful tools for quantifying the impacts of
sequence variation on gene expression. Reading out molecular phenotypes with …
sequence variation on gene expression. Reading out molecular phenotypes with …
Toward identification of functional sequences and variants in noncoding DNA
Understanding the noncoding part of the genome, which encodes gene regulation, is
necessary to identify genetic mechanisms of disease and translate findings from genome …
necessary to identify genetic mechanisms of disease and translate findings from genome …
Varipred: Enhancing pathogenicity prediction of missense variants using protein language models
Computational approaches for predicting the pathogenicity of genetic variants have
advanced in recent years. These methods enable researchers to determine the possible …
advanced in recent years. These methods enable researchers to determine the possible …