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Personalized single-cell networks: a framework to predict the response of any gene to any drug for any patient
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/1878-0261.12155openalex-snapshot
Emerging functions of the EGFR in cancer
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Computing Communities in Large Networks Using Random Walks
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The Information-Geometric Perspective of Compositional Data Analysis
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Application of Random Walks to Decentralized Recommender Systems
inferredcites →https://doi.org/10.1007/978-3-642-30220-6_25openalex-snapshot
Prioritizing Disease Genes by Bi-Random Walk
inferredcites →https://doi.org/10.1007/978-3-642-36809-7_2openalex-snapshot
Fundamental Concepts of Compositional Data Analysis
inferredcites →https://doi.org/10.1007/s00438-017-1374-5openalex-snapshot
A computational method using the random walk with restart algorithm for identifying novel epigenetic factors
inferredcites →https://doi.org/10.1007/s12064-015-0220-8openalex-snapshot
How should we measure proportionality on relative gene expression data?
inferredcites →https://doi.org/10.1016/j.bbadis.2017.11.021openalex-snapshot
Network-based method for mining novel HPV infection related genes using random walk with restart algorithm
inferredcites →https://doi.org/10.1016/j.compbiolchem.2015.02.008openalex-snapshot
Laplacian normalization and random walk on heterogeneous networks for disease-gene prioritization
inferredcites →https://doi.org/10.1016/j.isci.2019.03.021openalex-snapshot
Estimating Sample-Specific Regulatory Networks
inferredcites →https://doi.org/10.1016/j.protcy.2013.12.361openalex-snapshot
Random Walks based Image Segmentation Using Color Space Graphs
inferredcites →https://doi.org/10.1038/415530aopenalex-snapshot
Gene expression profiling predicts clinical outcome of breast cancer
inferredcites →https://doi.org/10.1038/75556openalex-snapshot
Gene Ontology: tool for the unification of biology
inferredcites →https://doi.org/10.1038/nrg.2015.16openalex-snapshot
Single-cell genome sequencing: current state of the science
inferredcites →https://doi.org/10.1038/nrg2626openalex-snapshot
Sequencing technologies — the next generation
inferredcites →https://doi.org/10.1038/s41556-018-0236-7openalex-snapshot
Tumour heterogeneity and metastasis at single-cell resolution
inferredcites →https://doi.org/10.1038/s41592-019-0372-4openalex-snapshot
Evaluating measures of association for single-cell transcriptomics
inferredcites →https://doi.org/10.1038/s41598-017-16520-0openalex-snapshot
propr: An R-package for Identifying Proportionally Abundant Features Using Compositional Data Analysis
inferredcites →https://doi.org/10.1039/c3mb70608gopenalex-snapshot
Inferring novel lncRNA–disease associations based on a random walk model of a lncRNA functional similarity network
inferredcites →https://doi.org/10.1073/pnas.0506580102openalex-snapshot
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
inferredcites →https://doi.org/10.1073/pnas.1609758114openalex-snapshot
BCL6 promotes glioma and serves as a therapeutic target
inferredcites →https://doi.org/10.1073/pnas.96.12.6745openalex-snapshot
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays
inferredcites →https://doi.org/10.1089/cmb.2014.0155openalex-snapshot
CSAX: Characterizing Systematic Anomalies in eXpression Data
inferredcites →https://doi.org/10.1093/bioinformatics/bty175openalex-snapshot
Understanding sequencing data as compositions: an outlook and review
inferredcites →https://doi.org/10.1093/bioinformatics/bty637openalex-snapshot
Random walk with restart on multiplex and heterogeneous biological networks
inferredcites →https://doi.org/10.1093/gigascience/giz107openalex-snapshot
A field guide for the compositional analysis of any-omics data
inferredcites →https://doi.org/10.1093/nar/30.1.207openalex-snapshot
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
inferredcites →https://doi.org/10.1093/nar/gkx1063openalex-snapshot
Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data
inferredcites →https://doi.org/10.1101/gr.222877.117openalex-snapshot
Assessing the reliability of spike-in normalization for analyses of single-cell RNA sequencing data
inferredcites →https://doi.org/10.1109/cvpr.2004.353openalex-snapshot
GCap: Graph-based Automatic Image Captioning
inferredcites →https://doi.org/10.1109/icdm.2006.70openalex-snapshot
Fast Random Walk with Restart and Its Applications
inferredcites →https://doi.org/10.1109/tcbb.2021.3076422openalex-snapshot
PAN: Personalized Annotation-Based Networks for the Prediction of Breast Cancer Relapse
inferredcites →https://doi.org/10.1109/tpami.2006.233openalex-snapshot
Random Walks for Image Segmentation
inferredcites →https://doi.org/10.1126/science.1254257openalex-snapshot
Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma
inferredcites →https://doi.org/10.1126/science.286.5439.531openalex-snapshot
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring
inferredcites →https://doi.org/10.1136/bmj.i1981openalex-snapshot
Sparse data bias: a problem hiding in plain sight
inferredcites →https://doi.org/10.1145/2414425.2414437openalex-snapshot
A modified random walk framework for handling negative ratings and generating explanations
inferredcites →https://doi.org/10.1145/2567948.2579244openalex-snapshot
Random walks in recommender systems
inferredcites →https://doi.org/10.1145/2808797.2808852openalex-snapshot
Community Detection in Multiplex Networks using Locally Adaptive Random Walks
inferredcites →https://doi.org/10.1186/1471-2105-9-559openalex-snapshot
WGCNA: an R package for weighted correlation network analysis
inferredcites →https://doi.org/10.1186/1752-0509-1-54openalex-snapshot
Eigengene networks for studying the relationships between co-expression modules
inferredcites →https://doi.org/10.1186/2049-2618-2-15openalex-snapshot
Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis
inferredcites →https://doi.org/10.1186/s12864-017-4338-6openalex-snapshot
InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk
inferredcites →https://doi.org/10.1186/s12918-018-0539-0openalex-snapshot
Improving the measurement of semantic similarity by combining gene ontology and co-functional network: a random walk based approach
inferredcites →https://doi.org/10.12688/f1000research.12223.1openalex-snapshot
recount workflow: Accessing over 70,000 human RNA-seq samples with Bioconductor
inferredcites →https://doi.org/10.12688/f1000research.7563.1openalex-snapshot
Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences
inferredcites →https://doi.org/10.1371/journal.pcbi.1004075openalex-snapshot
Proportionality: A Valid Alternative to Correlation for Relative Data
inferredcites →https://doi.org/10.2174/0929866525666180905104904openalex-snapshot
RWLPAP: Random Walk for lncRNA-protein Associations Prediction
inferredcites →https://doi.org/10.3389/fgene.2019.00599openalex-snapshot
Cancer as a Tissue Anomaly: Classifying Tumor Transcriptomes Based Only on Healthy Data
inferredcites →https://doi.org/10.3402/mehd.v26.27663openalex-snapshot
Analysis of composition of microbiomes: a novel method for studying microbial composition
inferredcites →https://doi.org/10.3892/mmr.2016.6058openalex-snapshot
Identification of key genes in colorectal cancer using random walk with restart
inferredcites →https://doi.org/10.48550/arxiv.1712.08865openalex-snapshot
Biological Systems as Heterogeneous Information Networks: A Mini-review and Perspectives
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1109/tcbb.2021.3076422openalex-snapshot
PAN: Personalized Annotation-Based Networks for the Prediction of Breast Cancer Relapse
inferred← citeshttps://doi.org/10.1145/3368555.3384449openalex-snapshot
Disease state prediction from single-cell data using graph attention networks
inferred← citeshttps://doi.org/10.1609/aaai.v35i6.16619openalex-snapshot
Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks
inferred← citeshttps://doi.org/10.48550/arxiv.2007.04777openalex-snapshot
Self-supervised edge features for improved Graph Neural Network training
inferred← citeshttps://doi.org/10.64898/2026.02.15.26346357openalex-snapshot
Combining phenotypic similarity and network propagation to improve performance and clinical consistency of rare disease diagnosis
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