|
0
|
|
CSIE: cancer subtyping via inference and ensemble.
(academic.oup.com)
|
Tran D
…
Nguyen T
Briefings in Bioinformatics
2026-05-04
|
#cancer
#clustering
#multi-omics
#classification
#inference
|
|
0
|
|
ModelistsGCN: a multimodal graph convolutional network framework for single-cell spatial transcriptomic cell typing.
(academic.oup.com)
|
Konforti N
…
Alon S
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#cell typing
#clustering
#morphology
#spatial omics
|
|
0
|
|
A scalable, multi-resolution consensus clustering approach for prioritizing robust signals from high-throughput screens.
(academic.oup.com)
|
Bao SC
…
Palpant NJ
Briefings in Bioinformatics
2026-05-04
|
#clustering
#screening
#unsupervised
#high-dimensional
|
|
0
|
|
MLN2SVG: domain-aware spatially variable gene detection using contrastive variational autoencoder and multi-level neighbor search.
(academic.oup.com)
|
Hussain S
…
Liu X
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#cancer
|
|
0
|
|
scMVAF: a multi-view adaptive fusion clustering approach for single-cell RNA-sequencing data.
(academic.oup.com)
|
Wang J
…
Liang Y
Briefings in Bioinformatics
2026-05-04
|
#clustering
#transcriptomics
#single-cell
#embedding
#autoencoder
|
|
0
|
|
Identifying batch-integrated domains from spatial transcriptomics via graph autoencoder with contrastive learning based on cross-modality and data augmentation.
(academic.oup.com)
|
Mao Y
…
Lyu Q
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#integration
#autoencoders
|
|
0
|
|
Biased multi-view contrastive learning with attentive masking for spatial transcriptomic analysis.
(academic.oup.com)
|
Fu L
…
Sun H
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#representation learning
#tissue architecture
#embedding
|
|
0
|
|
PVAED: prior-guided variational autoencoders with diffusion denoising for interpretable single-cell representation learning.
(academic.oup.com)
|
Niu Y
…
Ma W
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#dimensionality reduction
#clustering
#representation learning
#gene regulation
|
|
0
|
|
Semi-supervised disentangled representation learning for single-cell RNA sequencing data.
(academic.oup.com)
|
Liu H
…
Wei Z
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#modeling
#sequencing
|
|
0
|
|
On using clustering statistics for assessing plasmid binning tools accuracy.
(academic.oup.com)
|
Epain V
…
Chauve C
Briefings in Bioinformatics
2026-05-04
|
#plasmid
#clustering
#assembly
#metagenomics
#benchmarking
|
|
0
|
|
geneSCOPE: gene spatial co-occurrence of pairwise expression.
(academic.oup.com)
|
Zhang S
…
Haeno H
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#network
|
|
0
|
|
AnnQ: reference-based quantification of cellular abnormality at single-cell resolution.
(academic.oup.com)
|
Lee D
…
An JY
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#annotation
#perturbation
|
|
0
|
|
GatorSC: multi-scale cell and gene graphs with mixture-of-experts fusion for single-cell transcriptomics.
(academic.oup.com)
|
Liu Y
…
Bian J
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#representation learning
#graph neural network
|
|
0
|
|
GOLDEN fusion: a graph-oriented learning with domain-embedding network fusion for generating super gene sets in functional genomics.
(academic.oup.com)
|
Li Q
…
Yue Z
Briefings in Bioinformatics
2026-05-04
|
#genomics
#pathways
#clustering
#networks
#embedding
|
|
0
|
|
Lense: optimizing data preprocessing in single-cell omics using large language models.
(academic.oup.com)
|
Liu J
…
Ji Z
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#preprocessing
#clustering
#sequencing
|
|
0
|
|
A unified framework for selecting and evaluating cell-type-specific gene co-expressions in single-cell data.
(academic.oup.com)
|
Shan X
…
Zhao H
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#benchmarking
#coexpression
|
|
0
|
|
Empowering multifaceted analysis of spatial transcriptomics data with RGAST.
(academic.oup.com)
|
Gong Y
…
Yu Z
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#neuroimaging
#modeling
|
|
0
|
|
CEDR: robust consensus cancer subtyping with multi-omics data via ensemble dimensionality reduction.
(academic.oup.com)
|
Cao H
…
Cui Y
Briefings in Bioinformatics
2026-05-04
|
#clustering
#cancer
#dimensionality reduction
#multi-omics
#modeling
|
|
0
|
|
scMarkerGene: an interpretable neural network framework for cell-type-specific marker gene discovery.
(academic.oup.com)
|
Zhang J
…
Zhao Y
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#neural network
#cell-type
#heterogeneity
|
|
0
|
|
Toward the regularization of E value from BLAST similarity search into a dissimilarity measure as distance function, and the metrication of protein sequence space.
(academic.oup.com)
|
Mao B
Briefings in Bioinformatics
2026-05-04
|
#alignment
#homology
#sequencing
#clustering
|
|
0
|
|
STGAT: spatial domain identification of consecutive slices based on graph contrastive learning.
(academic.oup.com)
|
Feng Y
…
Jin S
Briefings in Bioinformatics
2026-05-04
|
#transcriptomics
#clustering
#graph learning
|