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0
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|
SIVA: diagonal integration of spatial multi-omics data via spatially informed variational autoencoders and anchor guidance.
(academic.oup.com)
|
Jiang P
…
Tian T
Bioinformatics
2026-07-01
|
#spatial omics
#machine learning
#integration
#multimodal
#transcriptomics
|
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0
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|
Towards the construction of a virtual yeast.
(nature.com)
|
Qian L
…
Guo T
Nature
2026-07-01
|
#systems biology
#modeling
#synthetic biology
#machine learning
|
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0
|
|
Fairness-aware supervised hierarchical contrastive semantic learning for sexual dimorphism analysis.
(academic.oup.com)
|
Ko E
…
Kang M
Bioinformatics
2026-07-01
|
#transcriptomics
#sexual dimorphism
#machine learning
#precision medicine
#cancer
|
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0
|
|
Bridging ancestry gaps in genomic risk prediction with tabular foundation models.
(academic.oup.com)
|
Das A
…
Cui Y
Bioinformatics
2026-07-01
|
#ancestry
#prediction
#polygenic risk
#machine learning
#genomics
|
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0
|
|
MOCDT: multi-cancer detection and tissue-of-origin classification via cfDNA multi-modal integration.
(academic.oup.com)
|
Kim G
…
Choi JH
Bioinformatics
2026-07-01
|
#circulating tumor dna
#cancer-detection
#machine learning
#multi-omics
#liquid biopsy
|
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0
|
|
Deciphering key factors of active learning performance in biomolecular design.
(academic.oup.com)
|
Zhi Y
…
Wang X
Bioinformatics
2026-07-01
|
#machine learning
#active learning
#optimization
#protein design
#genetic engineering
|
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0
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NPBIP: predicting binding preferences of uncharacterized nucleic-acid-binding proteins.
(academic.oup.com)
|
Shimshoviz N
…
Orenstein Y
Bioinformatics
2026-07-01
|
#machine learning
#protein-binding
#prediction
#rna
#dna
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0
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Improving hit discovery by integrating activity cliff sensitivity into active learning.
(academic.oup.com)
|
Kim J
…
Kim S
Bioinformatics
2026-07-01
|
#active learning
#machine learning
#drug discovery
#structure-activity
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0
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Agentomics: an agentic system that autonomously develops novel state-of-the-art solutions for biomedical machine learning tasks.
(academic.oup.com)
|
Martinek V
…
Alexiou P
Bioinformatics
2026-07-01
|
#machine learning
#automation
#genomics
#protein design
#drug discovery
|
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0
|
|
Knowledge-guided contextual gene set analysis with large language models.
(academic.oup.com)
|
Wang Z
…
Lu Z
Bioinformatics
2026-07-01
|
#pathway analysis
#transcriptomics
#machine learning
#oncology
|
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0
|
|
CROP: a feature-independent context-aware method for CRISPR-Cas9 frameshift prediction.
(academic.oup.com)
|
Tziony I
…
Orenstein Y
Bioinformatics
2026-07-01
|
#crispr
#genome editing
#machine learning
#prediction
|
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0
|
|
Foundation model enables interpretable open and error-tolerant searching for mass spectrometry-based proteomics.
(academic.oup.com)
|
Altenburg T
…
Renard BY
Bioinformatics
2026-07-01
|
#proteomics
#mass spectrometry
#ptm
#peptide-identification
#machine learning
|
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0
|
|
PhageMind: generalized strain-level phage host range prediction via meta-learning.
(academic.oup.com)
|
Shen Y
…
Shang J
Bioinformatics
2026-07-01
|
#phage
#phage-host-interactions
#machine learning
#prediction
#strain-typing
|
|
0
|
|
Integrating multi-type features and knowledge graph for graded prediction of drug-induced liver injury in humans.
(journals.plos.org)
|
Liu Y
…
Su R
PLOS Computational Biology
2026-07-01
|
#hepatotoxicity
#drug safety
#machine learning
#cheminformatics
#prediction
|
|
0
|
|
PUFFIN: protein unit discovery with functional supervision.
(academic.oup.com)
|
Uludogan G
…
Ozgur A
Bioinformatics
2026-07-01
|
#structure-function
#proteomics
#machine learning
#protein-domains
|
|
0
|
|
ATTNSOM: learning cross-isoform attention for cytochrome P450 site-of-metabolism prediction.
(academic.oup.com)
|
Kim H
…
Kang J
Bioinformatics
2026-07-01
|
#metabolism
#machine learning
#drug discovery
#prediction
|
|
0
|
|
How not to be seen: predicting unseen enzyme functions using contrastive learning.
(academic.oup.com)
|
Ma X
…
Li Q
Bioinformatics
2026-07-01
|
#enzyme
#protein function
#machine learning
#sequence prediction
#annotation
|
|
0
|
|
DNA-aware evaluation and debiasing of sequence-to-function models.
(academic.oup.com)
|
Cakmakci D
…
Li Y
Bioinformatics
2026-07-01
|
#machine learning
#sequencing
#epigenomics
#transcriptomics
#regulatory-genomics
|
|
0
|
|
EPIC: Event Prototyping via Information Constrained graph learning for personalized cancer driver gene prediction.
(academic.oup.com)
|
Cho SP
…
Cho YR
Bioinformatics
2026-07-01
|
#cancer
#driver mutations
#machine learning
#precision-oncology
#genomics
|
|
0
|
|
KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening.
(academic.oup.com)
|
Jang W
…
Shin WH
Bioinformatics
2026-07-01
|
#kinase
#virtual screening
#structure prediction
#machine learning
#drug discovery
|
|
0
|
|
seq2ribo: structure-aware integration of machine learning and simulation to predict ribosome location profiles from RNA sequences.
(academic.oup.com)
|
Kaynar G
…
Kingsford C
Bioinformatics
2026-07-01
|
#translation
#ribosome profiling
#machine learning
#rna structure
#simulation
|
|
0
|
|
PertAdapt: unlocking single-cell foundation models for genetic perturbation prediction via condition-sensitive adaptation.
(academic.oup.com)
|
Bai D
…
Xing EP
Bioinformatics
2026-07-01
|
#transcriptomics
#single-cell
#perturbation
#machine learning
#knockouts
|
|
0
|
|
Screening of core targets for Di(2-ethylhexyl) Phthalate-related gastric cancer based on machine learning, molecular docking, and SHAP analysis.
(journals.plos.org)
|
Li S
…
Huo B
PLOS Computational Biology
2026-07-01
|
#toxicology
#cancer
#machine learning
#docking
#pathways
|