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0
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NCBoost v2: a classifier for non-coding single-nucleotide variants in Mendelian diseases.
(academic.oup.com)
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Caron B
…
Rausell A
Bioinformatics
2026-05-03
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#pathogenicity
#variant
#machine learning
#non-coding
#mendelian
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0
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KG-bench: benchmarking graph neural network algorithms for drug repurposing.
(academic.oup.com)
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Wei S
…
't Hoen PAC
Bioinformatics
2026-05-03
|
#drug-repurposing
#machine learning
#knowledge graph
#benchmarking
#prediction
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0
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Learning protein representations with conformational dynamics.
(academic.oup.com)
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Kalifa D
…
Radinsky K
Bioinformatics
2026-05-03
|
#machine learning
#structure prediction
#modeling
#folding
#protein-protein interaction
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0
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CpGene: a web application for epigenetic signature identification from DNA methylation arrays.
(academic.oup.com)
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Lazaros K
…
Vrahatis AG
Bioinformatics
2026-05-03
|
#methylation
#epigenomics
#biomarker
#machine learning
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0
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Whole-genome prediction of bacterial pathogenic capacity on novel bacteria using protein language models with PathogenFinder2.
(academic.oup.com)
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Ferrer Florensa A
…
Aarestrup FM
Bioinformatics
2026-05-03
|
#virulence
#pathogenicity
#machine learning
#proteomics
#surveillance
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0
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BABAPPAlign: a multiple sequence alignment engine with a learned residue-level scoring function.
(academic.oup.com)
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Sinha K
Bioinformatics
2026-05-03
|
#alignment
#sequencing
#machine learning
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0
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Protein language model embeddings improve HIV drug resistance prediction: a comprehensive benchmark with attention-based interpretability.
(academic.oup.com)
|
Farquhar H
Bioinformatics
2026-05-03
|
#amr
#machine learning
#protein language models
#sequencing
#prediction
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0
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Molecular fingerprints are strong models for peptide function prediction.
(academic.oup.com)
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Adamczyk J
…
Czech W
Bioinformatics
2026-05-03
|
#peptide
#modeling
#machine learning
#molecular
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0
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A systematic review of machine learning on clinical MALDI-TOF MS.
(academic.oup.com)
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Schmidt-Santiago L
…
Gomez-Verdejo V
Briefings in Bioinformatics
2026-05-03
|
#machine learning
#amr
#diagnostics
#proteomics
#classification
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0
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When complexity does not pay: benchmarking deep learning and ensemble methods for biomarker discovery.
(academic.oup.com)
|
Njume CM
…
Cakmak A
Briefings in Bioinformatics
2026-05-03
|
#biomarker
#machine learning
#multi-omics
#feature selection
#deep learning
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0
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A cross-attentive multi-task graph learning framework for chemical reaction modeling.
(academic.oup.com)
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Astero M
…
Rousu J
Bioinformatics
2026-05-03
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#modeling
#chemistry
#machine learning
#graphs
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0
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MuFaDDG: a sequence-based multiscale feature fusion framework for protein stability changes prediction.
(academic.oup.com)
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Gong J
…
Bo X
Bioinformatics
2026-05-03
|
#protein design
#protein stability
#prediction
#machine learning
#mutation
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0
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dAMN: a genome-scale neural-mechanistic hybrid model to predict bacterial growth dynamics.
(academic.oup.com)
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Faulon JL
…
Asin-Garcia E
Bioinformatics
2026-05-03
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#modeling
#metabolism
#machine learning
#growth dynamics
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0
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HybridGNN: a graph neural network approach for human miRNA-disease association prediction.
(academic.oup.com)
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Ahmad B
…
Qi YC
Bioinformatics
2026-05-03
|
#microrna
#modeling
#prediction
#disease
#machine learning
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0
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Inferring the qualities of protein-RNA models with graph transformers.
(academic.oup.com)
|
Siciliano AJ
…
Wang Z
Bioinformatics
2026-05-03
|
#protein-rna
#modeling
#structure prediction
#machine learning
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0
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A framework to infer de novo exonic variants when parental genotypes are missing enhances association studies of autism.
(academic.oup.com)
|
Moon H
…
Roeder K
Bioinformatics
2026-05-03
|
#autism
#de novo variants
#association studies
#machine learning
#exome
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