Single-cell Interpretation via Multi-kernel Learning (R code in master branch, Matlab code in matlab branch), implementations of the method published in http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4207.html.

19 Research products, page 1 of 2

Revealing heterogeneity of brain imaging phenotypes in Alzheimer’s disease based on unsupervised clustering of blood marker profiles
2018IsRelatedTo
Identifying cell types from single-cell data based on similarities and dissimilarities between cells
2021IsRelatedTo
scSemiGCN: boosting cell-type annotation from noise-resistant graph neural networks with extremely limited supervision
2024IsRelatedTo
MarkovHC: Markov hierarchical clustering for the topological structure of high-dimensional single-cell omics data
2020IsRelatedTo
Single-Cell Transcriptomics Bioinformatics and Computational Challenges
2016IsRelatedTo
A quantitative framework for evaluating single-cell data structure preservation by dimensionality reduction techniques
2019IsRelatedTo
Essential procedures of single-cell RNA sequencing in multiple myeloma and its translational value
2023IsRelatedTo
Analysis and Visualization of Spatial Transcriptomic Data
2022IsRelatedTo
A Comparison for Dimensionality Reduction Methods of Single-Cell RNA-seq Data
2021IsRelatedTo
Visualization and analysis of single-cell RNA-seq data by kernel-based similarity learning
2016IsRelatedTo

chevron_left
1
2
chevron_right

Found an issue? Give us feedback

Beta

SDGs Suggest

3. Good health

Beta

SDGs:

3. Good health,

Related to Research communities

Knowmad Institut

Cancer Research