|
0
|
|
Accessibility in proteins and RNAs interactions prediction with machine learning: are we overlooking non-experts?
(academic.oup.com)
|
Florentino BR
…
F de Carvalho ACPL
Briefings in Bioinformatics
2026-05-04
|
#prediction
#protein-rna
#machine learning
#computational tools
|
|
0
|
|
Comparative review of artificial intelligence for transcriptomic biomarker discovery in coronavirus disease 2019 (COVID-19).
(academic.oup.com)
|
Khoo LY
…
Dhillon SK
Briefings in Bioinformatics
2026-05-04
|
#covid-19
#transcriptomics
#machine learning
#biomarker
#classification
|
|
0
|
|
MDCDR: predicting cancer drug response via multimodal feature fusion and feature disentanglement.
(academic.oup.com)
|
Zhang J
…
Shen X
Briefings in Bioinformatics
2026-05-04
|
#modeling
#cancer
#machine learning
#personalized medicine
#drug response
|
|
0
|
|
Foundation models and deep learning for cancer drug response prediction: a framework for data, metrics, and validation.
(academic.oup.com)
|
Sada Del Real K
…
Rubio A
Briefings in Bioinformatics
2026-05-04
|
#modeling
#cancer
#machine learning
#drug response
#omics
|
|
0
|
|
ac4C modification sites prediction in human mRNA: a complete review.
(academic.oup.com)
|
Zulfiqar H
…
Yu XL
Briefings in Bioinformatics
2026-05-04
|
#prediction
#epigenomics
#machine learning
#rna modification
|
|
0
|
|
The role of protein embeddings for protein-protein interaction prediction with graph neural networks.
(academic.oup.com)
|
Balbi L
…
Pesquita C
Briefings in Bioinformatics
2026-05-04
|
#machine learning
#protein-protein interaction
#embeddings
#graph neural network
|
|
0
|
|
MuFGPS: enhancing liquid-liquid phase separation protein prediction through multi-level features and ensemble learning.
(academic.oup.com)
|
Xian L
…
Wang Y
Briefings in Bioinformatics
2026-05-04
|
#prediction
#machine learning
#phase separation
#protein structure
#ensemble
|
|
0
|
|
Hypergraph learning with multi-dimensional metabolite feature extractions and static-dynamic attention mechanisms to fill missing reactions in metabolic networks.
(academic.oup.com)
|
Wang K
…
Zhou J
Briefings in Bioinformatics
2026-05-04
|
#modeling
#metabolism
#synthetic biology
#machine learning
|
|
0
|
|
Toward trustworthy artificial intelligence in multi-omics: a review of reproducibility, stability, and interpretability.
(academic.oup.com)
|
Vo TH
…
Le NQK
Briefings in Bioinformatics
2026-05-04
|
#machine learning
#multi-omics
#reproducibility
#precision medicine
#interpretability
|
|
0
|
|
MIFNDRA: an innovative knowledge-enhanced multimodal fusion and graph learning framework for predicting drug resistance-related ncRNAs.
(academic.oup.com)
|
Sui J
…
Guo J
Briefings in Bioinformatics
2026-05-04
|
#amr
#cancer
#prediction
#machine learning
#ncrna
|
|
0
|
|
Decoding disease and therapy through multiomics integration and systems analysis.
(academic.oup.com)
|
Mathew MJ
…
Zagury JF
Briefings in Bioinformatics
2026-05-04
|
#machine learning
#multi-omics
#integration
#biomarker
#precision medicine
|
|
0
|
|
Benchmarking computational methods for multi-omics biomarker discovery in cancer.
(academic.oup.com)
|
Li AZ
…
Liu R
Briefings in Bioinformatics
2026-05-04
|
#cancer
#machine learning
#multi-omics
#biomarker
#prognosis
|
|
0
|
|
Artificial Intelligence in genomics: a comprehensive survey of methods, resources, challenges, and prospects.
(academic.oup.com)
|
Ishtyaq Mahmud M
…
Banerjee T
Briefings in Bioinformatics
2026-05-04
|
#gene expression
#machine learning
#deep learning
#precision medicine
#variant detection
|
|
0
|
|
Contemporary data-driven innovations in peptide-based therapeutic design.
(academic.oup.com)
|
Priyadarsinee L
…
Murugan NA
Briefings in Bioinformatics
2026-05-04
|
#therapeutics
#machine learning
#peptide
#drug design
|
|
0
|
|
Cross-modality representation and multi-sample integration of spatially resolved omics data.
(academic.oup.com)
|
Li Z
…
Jiang R
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#machine learning
#multi-omics
#integration
|
|
0
|
|
DADA-EV: domain-adaptive diffusion autoencoder for estimating tissue- and cell-type-specific origin in extracellular vesicle transcriptomes.
(academic.oup.com)
|
Liao S
…
Dong M
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#machine learning
#extracellular vesicles
#deconvolution
#liquid biopsy
|
|
0
|
|
GraphLooper: predicting chromatin loops based on hierarchical multi-view graph pooling method.
(academic.oup.com)
|
Wang S
…
Huang DS
Briefings in Bioinformatics
2026-05-04
|
#modeling
#chromatin
#machine learning
#gene regulation
|
|
0
|
|
Out-of-distribution generalization enhances protein function annotation for low-homology sequences.
(academic.oup.com)
|
Fu Y
…
Deng M
Briefings in Bioinformatics
2026-05-04
|
#machine learning
#drug discovery
#structure prediction
#protein function annotation
|
|
0
|
|
Computational paradigms for antimicrobial resistance prediction: integrating multi-omics, structural modeling, and foundation artificial intelligence systems.
(academic.oup.com)
|
Hossain E
…
Yousefi N
Briefings in Bioinformatics
2026-05-04
|
#genomics
#modeling
#amr
#prediction
#machine learning
|
|
0
|
|
Cytokine-driven immunogenicity prediction: integrating HLA binding and cytokine induction.
(academic.oup.com)
|
Gavrilenko A
…
Shashkova T
Briefings in Bioinformatics
2026-05-04
|
#machine learning
#immunogenicity
#cytokine
#peptide
#hla
|
|
0
|
|
A novel machine learning-based algorithm for eQTL identification reveals complex pleiotropic effects in the MHC region.
(academic.oup.com)
|
Li RY
…
Qin ZS
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#machine learning
#eqtl
#variant
#pleiotropy
|
|
0
|
|
MAPLE: interpretable deep learning identifies selective antimicrobial peptides using joint evolutionary-physicochemical analysis.
(academic.oup.com)
|
Liu H
…
Yu G
Briefings in Bioinformatics
2026-05-04
|
#prediction
#machine learning
#toxicity
#antimicrobial peptides
#selectivity
|
|
0
|
|
ProtDML: label-aware representation learning for broad-spectrum protein function prediction.
(academic.oup.com)
|
Kan Y
…
Yi G
Briefings in Bioinformatics
2026-05-04
|
#proteomics
#machine learning
#annotation
#classification
#multifunctionality
|
|
0
|
|
Decoding extremophiles: insights from bioinformatics, machine learning, and data-driven approaches.
(academic.oup.com)
|
Chasapi MN
…
Soares Rosado A
Briefings in Bioinformatics
2026-05-04
|
#proteomics
#metabolism
#metagenomics
#machine learning
#extremophiles
|
|
0
|
|
Rethinking bioinformatics in liquid-liquid phase separation: data resources, predictive models, and an event-centric perspective.
(academic.oup.com)
|
Yuan ZL
…
Ning L
Briefings in Bioinformatics
2026-05-04
|
#bioinformatics
#modeling
#prediction
#machine learning
|
|
0
|
|
CRISPR-MBTF: a multi-branch transformer fusion framework for CRISPR-Cas9 off-target prediction.
(academic.oup.com)
|
Jahangiri-Sisakht A
…
Alipanahi R
Briefings in Bioinformatics
2026-05-04
|
#prediction
#crispr
#machine learning
#genome editing
#off-target
|
|
0
|
|
KSDiffusion: conditional diffusion for kinase-specific phosphorylation site prediction under data-limited and imbalanced regimes.
(academic.oup.com)
|
Qiu S
…
Shi X
Briefings in Bioinformatics
2026-05-04
|
#modeling
#proteomics
#machine learning
#phosphorylation
|
|
0
|
|
Computational prediction of replication origins: a comparative review of methods, benchmarks, and trends from heuristics to deep learning.
(academic.oup.com)
|
Jomaa H
…
Assaf R
Briefings in Bioinformatics
2026-05-04
|
#genomics
#prediction
#machine learning
#replication
#benchmarking
|
|
0
|
|
Deep Prior Framework: integrating functional specificity with general plausibility for targeted protein evolution.
(academic.oup.com)
|
Zhang S
…
Zheng X
Briefings in Bioinformatics
2026-05-04
|
#computational modeling
#machine learning
#mutation
#protein design
#directed evolution
|
|
0
|
|
Artificial intelligence in drug research and development: a review of methods and applications in drug repurposing.
(academic.oup.com)
|
Zielinska A
…
Souto EB
Briefings in Bioinformatics
2026-05-04
|
#prediction
#networks
#machine learning
#drug discovery
#repurposing
|
|
0
|
|
Reflections on the use of LLMs for cell annotation.
(academic.oup.com)
|
Ray PP
Briefings in Bioinformatics
2026-05-04
|
#bioinformatics
#transcriptomics
#machine learning
#annotation
|
|
0
|
|
Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.
(academic.oup.com)
|
Sardar S
…
Dutta S
Briefings in Bioinformatics
2026-05-04
|
#amr
#machine learning
#validation
#stewardship
#interpretability
|
|
0
|
|
CLABP: a contrastive learning framework integrating protein language models and structural information for antibacterial peptide prediction.
(academic.oup.com)
|
Zhou X
…
Lv J
Briefings in Bioinformatics
2026-05-04
|
#amr
#peptide
#machine learning
#protein structure
|
|
0
|
|
A knowledge-guided deep learning framework for quantitative nucleic acid testing.
(academic.oup.com)
|
Yang J
…
Zhang D
Briefings in Bioinformatics
2026-05-04
|
#pcr
#diagnostics
#sequencing
#machine learning
|