|
0
|
|
Unveiling patterns: an exploration of machine learning techniques for unsupervised feature selection in single-cell data.
(academic.oup.com)
|
Chatterjee N
…
Alimadadi A
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#dimensionality reduction
#machine learning
|
|
0
|
|
CTAS: a network control theory-based approach to identify key regulatory TFs of AS events during epithelial-mesenchymal transition.
(academic.oup.com)
|
Gan Y
…
Qiu Y
Briefings in Bioinformatics
2026-01-07
|
#splicing
#emt
#transcriptomics
#network inference
#metastasis
|
|
0
|
|
Advances in scCUT&Tag and computational analysis for single-cell gene regulatory element mapping.
(academic.oup.com)
|
Wu J
…
Wang J
Briefings in Bioinformatics
2026-01-07
|
#epigenomics
#single-cell
#chromatin
#transcriptomics
#computational
|
|
0
|
|
A comprehensive survey of genome language models in bioinformatics.
(academic.oup.com)
|
Shu L
…
Zhang D
Briefings in Bioinformatics
2026-01-07
|
#modeling
#sequencing
#transcriptomics
#phylogenomics
|
|
0
|
|
Spatial information matters: are traditional imputation methods effective for spatial transcriptomics data?
(academic.oup.com)
|
Hafiz F
…
Shatabda S
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#imputation
#dropout
#clustering
|
|
0
|
|
NanoPrePro: a fully equipped, fast, and memory-efficient preprocessor for nanopore transcriptomic sequencing.
(academic.oup.com)
|
Chu CC
…
Lin YJ
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#sequencing
#preprocessing
#nanopore
|
|
0
|
|
Exploring potential transcription factors and their regulatory relationships based on asymmetric covariance natural vector encoding method and machine learning algorithms.
(academic.oup.com)
|
Hu G
…
Yau SS
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#machine learning
#prediction
#gene regulation
|
|
0
|
|
Replication stress-inducing ELF3 upregulation promotes BRCA1-deficient breast tumorigenesis in luminal progenitors.
(elifesciences.org)
|
Zhou J
…
Wang J
eLife
2026-01-07
|
#tumorigenesis
#replication stress
#transcriptomics
#genomic instability
|
|
0
|
|
PathCLAST: pathway-augmented contrastive learning with attention for interpretable spatial transcriptomics.
(academic.oup.com)
|
Noh M
…
Lim S
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#pathway
#tumor
|
|
0
|
|
Emerging insights into enhancer RNAs: biogenesis, function, mechanism, and disease implication.
(academic.oup.com)
|
Qiu M
…
Liao Q
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#gene regulation
#cancer
#therapeutic target
#ncrna
|
|
0
|
|
Cross-dataset transcriptomic analyses identify a conserved ENPP2+ macrophage-fibroblast activation axis in hypertrophic cardiomyopathy.
(academic.oup.com)
|
Huang F
…
Jin W
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#fibrosis
#cardiomyopathy
#macrophage
#inflammation
|
|
0
|
|
3D reconstruction of spatial transcriptomics with spatial pattern enhanced graph convolutional neural network.
(academic.oup.com)
|
Tang C
…
Xu L
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#reconstruction
#neural network
#clustering
|
|
0
|
|
Revealing shared molecular markers and mechanisms in colorectal cancer and COVID-19 through bioinformatics and machine learning.
(academic.oup.com)
|
Wang H
…
Zhao L
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#machine learning
#immunity
#cancer
#infection
|
|
0
|
|
BayesRare: Bayesian mixture model for population-level rare cell type detection in multi-subject single-cell RNA sequencing data.
(academic.oup.com)
|
Yan Y
…
Wu H
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#modeling
#immunity
|
|
0
|
|
Detection of alternative splicing: deep sequencing or deep learning?
(academic.oup.com)
|
Hackl LM
…
Tsoy O
Briefings in Bioinformatics
2026-01-07
|
#splicing
#transcriptomics
#deep learning
#sequencing
#prediction
|
|
0
|
|
GFSeeker: a splicing-graph-based approach for accurate gene fusion detection from long-read RNA sequencing data.
(academic.oup.com)
|
Wang B
…
Jiang T
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#sequencing
#cancer
#fusion
#modeling
|
|
0
|
|
Adaptive multi-view information bottleneck for multi-omics data clustering.
(academic.oup.com)
|
Tian Z
…
Fu S
Briefings in Bioinformatics
2026-01-07
|
#clustering
#single-cell
#multi-omics
#transcriptomics
#modeling
|
|
0
|
|
SGCRNA: spectral clustering-guided co-expression network analysis without scale-free constraints for multi-omic data.
(academic.oup.com)
|
Osone T
…
Takarada T
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#network analysis
#biomarker
|
|
0
|
|
UBD: incorporating uncertainty in cell type proportion estimates from bulk samples to infer cell-type-specific profiles.
(academic.oup.com)
|
Cheng Y
…
Zhao H
Briefings in Bioinformatics
2026-01-07
|
#deconvolution
#transcriptomics
#bayesian
#clustering
|
|
0
|
|
A co-evolutionary perspective on humans and Mycobacterium tuberculosis in the era of systems biology.
(elifesciences.org)
|
Reichmann MT
…
Elkington PT
eLife
2026-01-07
|
#transcriptomics
#immunity
#pathogen
#modeling
#tb
|
|
0
|
|
Human messenger RNA harbors widespread noncoding splice isoforms.
(academic.oup.com)
|
Shi Q
…
He X
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#splicing
#cancer
#isoforms
#ncrna
|
|
0
|
|
Personalized gene expression prediction in the era of deep learning: a review.
(academic.oup.com)
|
Dubey V
…
Shen L
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#modeling
#genomics
#machine learning
|
|
0
|
|
Imputing missing values in single-cell RNA-sequencing data: a statistical and machine learning-based approach.
(academic.oup.com)
|
Shamsuzzaman AFM
…
Mukhopadhyay A
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#imputation
#clustering
#modeling
|
|
0
|
|
Ab initio detection of multiple epitranscriptomic modifications from Oxford nanopore technology direct RNA sequencing data.
(academic.oup.com)
|
Fonzino A
…
Picardi E
Briefings in Bioinformatics
2026-01-07
|
#sequencing
#basecalling
#transcriptomics
#epigenomics
|
|
0
|
|
ASTWAS: modeling alternative polyadenylation and SNP effects in kernel-driven TWAS reveal novel genetic associations for complex traits.
(academic.oup.com)
|
Wang Y
…
Cao C
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#twas
#modeling
#immunity
#genetics
|
|
0
|
|
Computational approaches to multimodal data integration in rheumatoid arthritis: from data landscape to clinical translation.
(academic.oup.com)
|
Xu D
…
Wen C
Briefings in Bioinformatics
2026-01-07
|
#integration
#machine learning
#rheumatoid arthritis
#proteomics
#transcriptomics
|
|
0
|
|
Advances and challenges in single-cell RNA sequencing data analysis: a comprehensive review.
(academic.oup.com)
|
Nesari AM
…
Ghorbian S
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#preprocessing
#immunity
#modeling
|
|
0
|
|
MoAGNN: a multi-omics hierarchical graph neural network for subtype classification and prognosis prediction in lung adenocarcinoma.
(academic.oup.com)
|
Lin CP
…
Lee TY
Briefings in Bioinformatics
2026-01-07
|
#cancer
#multi-omics
#modeling
#prognosis
#transcriptomics
|
|
0
|
|
scGACL: a generative adversarial network with multi-scale contrastive learning for accurate single-cell RNA sequencing imputation.
(academic.oup.com)
|
Jiang Y
…
Guo F
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#imputation
#sequencing
#modeling
|
|
0
|
|
SHEST: single-cell-level artificial intelligence from haematoxylin and eosin morphology for cell-type prediction and spatial transcriptomics reconstruction.
(academic.oup.com)
|
Jeong H
…
Choi YL
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#morphology
#cancer
#clustering
|
|
0
|
|
Revealing hidden regulatory dependencies: multi-perspective graph learning for single-cell gene regulatory network inference.
(academic.oup.com)
|
He W
…
Guo F
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#single-cell
#inference
#gene regulation
#graph neural network
|
|
0
|
|
An unsupervised method for spatial transcriptomics analysis based on adversarial autoencoder.
(academic.oup.com)
|
Lan W
…
Pan Y
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#denoising
|
|
0
|
|
Signal-based spatial domain identification of spatially resolved transcriptomics with multigraph fusion.
(academic.oup.com)
|
Ma Y
…
Ma X
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#clustering
#cancer
|
|
0
|
|
EpiXFormer: a cross-attention neural network for predicting cell type-specific transcription factor binding sites.
(academic.oup.com)
|
Peng Y
…
Zhao X
Briefings in Bioinformatics
2026-01-07
|
#transcriptomics
#epigenomics
#modeling
#machine learning
|
|
0
|
|
Harnessing AI to fuse phenotypic signatures for drug target identification: progress in computational modeling.
(academic.oup.com)
|
Chen F
…
Tang Z
Briefings in Bioinformatics
2026-01-07
|
#modeling
#transcriptomics
#drug discovery
#machine learning
#target prediction
|