|
0
|
|
MitoClipSplice: a machine learning framework for resolving mitochondrial RNA cleavage sites from strand-specific RNA-seq soft-clips.
(academic.oup.com)
|
Yuan Q
…
Zhou K
Briefings in Bioinformatics
2026-07-03
|
#transcriptomics
#rna-seq
#mitochondrial
#machine learning
#rna processing
|
|
0
|
|
Functional motif detection via in silico ablation using AlphaGenome.
(academic.oup.com)
|
Liang Y
…
Wang G
Briefings in Bioinformatics
2026-07-03
|
#regulation
#sequencing
#machine learning
#enhancer
#transcriptomics
|
|
0
|
|
Sparsity is all you need: rethinking biologically informed neural networks.
(academic.oup.com)
|
Caranzano I
…
Sanavia T
Briefings in Bioinformatics
2026-07-03
|
#machine learning
#neural network
#bioinformatics
#interpretability
#pathways
|
|
0
|
|
Graph-based drug-target interaction modeling: from representation learning to output-driven drug discovery.
(academic.oup.com)
|
Nguyen T
…
Nguyen G
Briefings in Bioinformatics
2026-07-03
|
#machine learning
#drug discovery
#computational modeling
#protein-interactions
#deep learning
|
|
0
|
|
Data-intensive immune network modelling for One Health.
(academic.oup.com)
|
Hillis R
…
Overton IM
Briefings in Bioinformatics
2026-07-03
|
#immunology
#bioinformatics
#transcriptomics
#machine learning
#network-biology
|
|
0
|
|
DeepACPred: an integrated multistage framework for anticancer peptide discovery and activity prediction.
(academic.oup.com)
|
Zhang B
…
Jia L
Briefings in Bioinformatics
2026-07-03
|
#cancer
#peptide
#machine learning
#drug discovery
#prediction
|
|
0
|
|
A chromatin-structure-guided framework for predictive and interpretable regulatory genomics.
(academic.oup.com)
|
Ye B
…
Liang J
Briefings in Bioinformatics
2026-07-03
|
#chromatin
#gene regulation
#machine learning
#3d genome
#epigenomics
|
|
0
|
|
Structure-aware artificial intelligence for next-generation drug discovery: from protein-ligand modeling to generative biomolecular design.
(academic.oup.com)
|
Yoon H
…
Lee Y
Briefings in Bioinformatics
2026-07-03
|
#protein structure
#drug discovery
#machine learning
#molecular design
#docking
|
|
0
|
|
AbTune: layer-wise selective fine-tuning of protein language models for antibodies.
(academic.oup.com)
|
Xu X
…
Bonvin AMJJ
Briefings in Bioinformatics
2026-07-03
|
#antibody
#proteomics
#machine learning
#protein structure
#affinity
|
|
0
|
|
Foundation models in omics research: a comprehensive survey.
(academic.oup.com)
|
Liu H
…
Sun J
Briefings in Bioinformatics
2026-07-03
|
#omics
#machine learning
#multi-omics
#transcriptomics
#biomarker
|
|
0
|
|
Accurate prediction of asparagine deamidation in biologics using advanced machine learning models.
(academic.oup.com)
|
Ahmed S
…
Pouryahya M
Briefings in Bioinformatics
2026-07-03
|
#deamidation
#machine learning
#protein-therapeutics
#prediction
#protein stability
|
|
0
|
|
miRSiC: a regulatory-aware machine learning framework for microRNA expression inference across bulk and single-cell transcriptomes.
(academic.oup.com)
|
Chen GT
…
Lee TY
Briefings in Bioinformatics
2026-07-03
|
#transcriptomics
#microrna
#cancer
#machine learning
#gene regulation
|
|
0
|
|
Reliable evaluation and learning in multi-input biological association prediction.
(academic.oup.com)
|
Ahmadian S
…
Montazeri H
Briefings in Bioinformatics
2026-07-03
|
#prediction
#drug target
#synergy
#machine learning
#interaction
|
|
0
|
|
Advancing bioinformatics with language models: components, applications, and perspectives.
(academic.oup.com)
|
Liu J
…
Zhou X
Briefings in Bioinformatics
2026-07-03
|
#bioinformatics
#machine learning
#genomics
#proteomics
#drug discovery
|
|
0
|
|
Deep learning models for cell cycle phase prediction from single-cell RNA sequencing data.
(academic.oup.com)
|
Akhter H
…
Adjeroh DA
Briefings in Bioinformatics
2026-07-03
|
#transcriptomics
#machine learning
#cell cycle
#deep learning
|
|
0
|
|
DeepAden: an explainable machine learning method for predicting the substrate specificity of nonribosomal peptide synthetases.
(academic.oup.com)
|
Huang J
…
Qin Z
Nucleic Acids Research
2026-07-03
|
#machine learning
#nonribosomal peptides
#biosynthesis
#substrate-specificity
#natural products
|
|
0
|
|
IRCAS: a novel end-to-end approach to identify, rectify, and classify comprehensive alternative splicing events in a transcriptome without genome reference.
(academic.oup.com)
|
Shen C
…
Zhang R
Briefings in Bioinformatics
2026-07-03
|
#transcriptomics
#splicing
#machine learning
#non-model-organisms
|
|
0
|
|
K-attention: a biologically informed attention operator for data-efficient sequence-based omics modeling.
(academic.oup.com)
|
Liu T
…
Gao G
Briefings in Bioinformatics
2026-07-03
|
#deep learning
#omics
#sequence modeling
#attention-mechanisms
#machine learning
|
|
0
|
|
T-cell receptor alpha to beta chains binding prediction.
(academic.oup.com)
|
Siminovsky D
…
Louzoun Y
Briefings in Bioinformatics
2026-07-03
|
#tcr
#prediction
#machine learning
#immunology
#sequencing
|
|
0
|
|
Mitigating negative data bias to enhance TCR-epitope binding and residue interaction prediction.
(academic.oup.com)
|
Mi X
…
Xiao Z
Briefings in Bioinformatics
2026-07-03
|
#immunotherapy
#machine learning
#binding
#prediction
#immunology
|
|
0
|
|
A historical journey of metabolite-protein interaction discovery: from data harmonization to AI-driven prediction.
(academic.oup.com)
|
Lawrence T
…
Gul L
Briefings in Bioinformatics
2026-07-03
|
#metabolomics
#proteomics
#cheminformatics
#bioinformatics
#machine learning
|
|
0
|
|
The critical role of artificial intelligence and bioinformatics in accelerating peptide-based vaccine discovery for tackling global infectious diseases.
(academic.oup.com)
|
Tholo N
…
Shukla P
Briefings in Bioinformatics
2026-07-03
|
#vaccinology
#immunoinformatics
#machine learning
#epitope
#immunogenicity
|
|
0
|
|
Generalizable AI predicts immunotherapy outcomes across cancers and treatments.
(nature.com)
|
Shen W
…
Zitnik M
Nature Medicine
2026-07-03
|
#transcriptomics
#cancer
#immunotherapy
#machine learning
#biomarker
|
|
0
|
|
Decoding viral protein sequences by large language models.
(academic.oup.com)
|
Fei T
…
Zeng T
Briefings in Bioinformatics
2026-07-03
|
#machine learning
#virology
#proteomics
#variant prediction
#immunology
|
|
0
|
|
RLASON-CDR: a reinforcement learning-driven adaptive synergistic optimization network for cancer drug response prediction.
(academic.oup.com)
|
Teng Z
…
Wang G
Briefings in Bioinformatics
2026-07-03
|
#machine learning
#drug response
#pharmacogenomics
#cancer
#precision medicine
|
|
0
|
|
Annotation-free phenotype prediction using knowledge-augmented clustering from single-cell RNA sequencing data.
(academic.oup.com)
|
Noh J
…
Oh M
Briefings in Bioinformatics
2026-07-03
|
#transcriptomics
#clustering
#phenotype
#machine learning
|
|
0
|
|
Computational prediction of RNA modification site-disease associations: a systematic review.
(academic.oup.com)
|
Ao C
…
Jia L
Briefings in Bioinformatics
2026-07-03
|
#epigenomics
#rna modification
#prediction
#machine learning
#computational
|
|
0
|
|
Hierarchical Multi-Omics Trajectory Prediction for fecal microbiota transplantation: a novel machine learning framework for small-sample longitudinal multi-omics integration.
(academic.oup.com)
|
Yi-Hui Z
…
George S
Briefings in Bioinformatics
2026-07-03
|
#microbiome
#metagenomics
#machine learning
#lipidomics
#longitudinal
|
|
0
|
|
Evidence-aware comparison of sequence-centric machine learning for antibody discovery and optimization.
(academic.oup.com)
|
Zhao J
…
Xie H
Briefings in Bioinformatics
2026-07-03
|
#antibody
#machine learning
#optimization
#sequencing
#design
|
|
0
|
|
Uncovering species- and drug-class-specific antimicrobial resistance mechanisms from large-scale whole-genome sequencing data using discordance analysis and machine learning.
(academic.oup.com)
|
Cheon NJ
…
Unno T
Briefings in Bioinformatics
2026-07-03
|
#amr
#sequencing
#machine learning
#genotype-phenotype
#annotation
|
|
0
|
|
FireProtASR 2.0: evolution-guided Design of Protein Ancestors and Successors with phylogenetics and machine learning.
(academic.oup.com)
|
Kohout P
…
Bednar D
Briefings in Bioinformatics
2026-07-03
|
#protein design
#ancestral reconstruction
#machine learning
#phylogenetics
#thermostability
|
|
0
|
|
DUET: a graph-based workflow for TCR-epitope prioritization and tumor-reactive T-cell identification.
(academic.oup.com)
|
Chen Y
…
Luo P
Briefings in Bioinformatics
2026-07-03
|
#immunotherapy
#epitope
#tcr
#machine learning
#computational
|