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Found 6 papers, 5 papers with code
Inferring cell-specific lncRNA regulation with single-cell RNA-sequencing data in the developing human neocortex
However, to analyze lncRNA regulation regarding individual cells, we focus on single-cell RNA-sequencing (scRNA-seq) data instead of bulk data.
Unveiling interpretable development-specific gene signatures in the developing human prefrontal cortex with ICGS
In this paper, to unveil interpretable development-specific gene signatures in human PFC, we propose a novel gene selection method, named Interpretable Causality Gene Selection (ICGS), which adopts a Bayesian Network (BN) to represent causality between multiple gene variables and a development variable.
LSEC: Large-scale spectral ensemble clustering
In LSEC, a large-scale spectral clustering based efficient ensemble generation framework is designed to generate various base clusterings within a low computational complexity.
Divide-and-conquer based Large-Scale Spectral Clustering
In this paper, we propose a divide-and-conquer based large-scale spectral clustering method to strike a good balance between efficiency and effectiveness.
Ranked #2 on
Image/Document Clustering
on pendigits
Ensemble Learning for Spectral Clustering
Instead of directly using the clustering results obtained from each base spectral clustering algorithm, the proposed method learns a robust presentation of graph Laplacian by ensemble learning from the spectral embedding of each base spectral clustering algorithm.
Ranked #1 on
Image/Document Clustering
on Wine
Multiclass spectral feature scaling method for dimensionality reduction
Irregular features disrupt the desired classification.
