Robust Graph Regularized NMF with Dissimilarity and Similarity Constraints for ScRNA-seq Data Clustering
Sign Up to like & getrecommendations! Published in 2022 at "Journal of chemical information and modeling"
DOI: 10.1021/acs.jcim.2c01305
Abstract: The notable progress in single-cell RNA sequencing (ScRNA-seq) technology is beneficial to accurately discover the heterogeneity and diversity of cells. Clustering is an extremely important step during the ScRNA-seq data analysis. However, it cannot achieve… read more here.
Keywords: seq data; graph regularized; robust graph; scrna seq ... See more keywords
Multiview Robust Graph-Based Clustering for Cancer Subtype Identification
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2022.3143897
Abstract: Cancer subtype identification is to classify cancer into groups according to their molecular characteristics and clinical manifestations and is the basis for more personalized diagnosis and therapy. Public datasets such as The Cancer Genome Atlas… read more here.
Keywords: cancer subtype; subtype identification; graph; graph based ... See more keywords
Joint Transformation Learning via the L2,1-Norm Metric for Robust Graph Matching
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2019.2912718
Abstract: Establishing correspondence between two given geometrical graph structures is an important problem in computer vision and pattern recognition. In this paper, we propose a robust graph matching (RGM) model to improve the effectiveness and robustness… read more here.
Keywords: robust graph; joint transformation; transformation learning; graph ... See more keywords
Ridge-Regression-Induced Robust Graph Relational Network.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3163412
Abstract: Graph convolutional networks (GCNs) have attracted increasing research attention, which merits in its strong ability to handle graph data, such as the citation network or social network. Existing models typically use first-order neighborhood information to… read more here.
Keywords: regression; robust graph; relational network; graph ... See more keywords
Scalable robust graph and feature extraction for arbitrary vessel networks in large volumetric datasets
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DOI: 10.1186/s12859-021-04262-w
Abstract: Background Recent advances in 3D imaging technologies provide novel insights to researchers and reveal finer and more detail of examined specimen, especially in the biomedical domain, but also impose huge challenges regarding scalability for automated… read more here.
Keywords: vessel networks; vessel; scalable robust; topology ... See more keywords
A robust graph-based computational model for predicting drug-induced liver injury compounds
Sign Up to like & getrecommendations! Published in 2025 at "PeerJ Computer Science"
DOI: 10.7717/peerj-cs.3416
Abstract: Drug-induced liver injury (DILI) is a leading cause of drug development failures and post-market withdrawals, presenting significant challenges to both pharmaceutical safety and clinical care. Conventional screening methods, such as laboratory-based cell assays and animal… read more here.
Keywords: drug induced; drug; liver injury; model ... See more keywords