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Network Propagation-based Prioritization of Long Tail Genes in 17 Cancer Types

https://doi.org/10.1101/2021.02.05.429983

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Defining a Cancer Dependency Map

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Comprehensive Characterization of Cancer Driver Genes and Mutations

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Oncogenic Signaling Pathways in The Cancer Genome Atlas

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Passenger Mutations in More Than 2,500 Cancer Genomes: Overall Molecular Functional Impact and Consequences

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Identification of FUBP1 as a Long Tail Cancer Driver and Widespread Regulator of Tumor Suppressor and Oncogene Alternative Splicing

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Network-Based Coverage of Mutational Profiles Reveals Cancer Genes

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Scalable Open Science Approach for Mutation Calling of Tumor Exomes Using Multiple Genomic Pipelines

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Exploiting rare driver mutations for precision cancer medicine

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‘Latent drivers’ expand the cancer mutational landscape

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Mutational heterogeneity in cancer and the search for new cancer-associated genes

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Pan-cancer network analysis identifies combinations of rare somatic mutations across pathways and protein complexes

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Network-based stratification of tumor mutations

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Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt

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The mini-driver model of polygenic cancer evolution

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Network propagation: a universal amplifier of genetic associations

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Improved estimation of cancer dependencies from large-scale RNAi screens using model-based normalization and data integration

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Pan-cancer analysis of whole genomes

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The long tail of oncogenic drivers in prostate cancer

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CancerMine: a literature-mined resource for drivers, oncogenes and tumor suppressors in cancer

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Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap

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Unifying cancer and normal RNA sequencing data from different sources

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Tug-of-war between driver and passenger mutations in cancer and other adaptive processes

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Deeper Inside PageRank

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Algorithms for Detecting Significantly Mutated Pathways in Cancer

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V avien : An Algorithm for Prioritizing Candidate Disease Genes Based on Topological Similarity of Proteins in Interaction Networks

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Mining gene functional networks to improve mass-spectrometry-based protein identification

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DAVID-WS: a stateful web service to facilitate gene/protein list analysis

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Discovering causal pathways linking genomic events to transcriptional states using Tied Diffusion Through Interacting Events (TieDIE)

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New directions for diffusion-based network prediction of protein function: incorporating pathways with confidence

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Hierarchical HotNet: identifying hierarchies of altered subnetworks

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ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

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COSMIC: the Catalogue Of Somatic Mutations In Cancer

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HumanNet v2: human gene networks for disease research

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STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

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Circos: An information aesthetic for comparative genomics

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Prioritizing candidate disease genes by network-based boosting of genome-wide association data

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Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

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Rare driver mutations in head and neck squamous cell carcinomas converge on NOTCH signaling

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Driver and Passenger Mutations in Cancer

inferredcites →https://doi.org/10.1158/0008-5472.can-15-3283-topenalex-snapshot

The Damaging Effect of Passenger Mutations on Cancer Progression

inferredcites →https://doi.org/10.1158/2159-8290.cd-11-0116openalex-snapshot

New Routes to Old Places: PIK3R1 and PIK3R2 Join PIK3CA and PTEN as Endometrial Cancer Genes

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Candidate gene prioritization by network analysis of differential expression using machine learning approaches

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DA DA: Degree-Aware Algorithms for Network-Based Disease Gene Prioritization

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The novel circ_0028171/miR-218-5p/IKBKB axis promotes osteosarcoma cancer progression

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Type 2 Diabetes Mellitus and Cancer: The Role of Pharmacotherapy

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Associating Genes and Protein Complexes with Disease via Network Propagation

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Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer

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Prediction and Validation of Gene-Disease Associations Using Methods Inspired by Social Network Analyses

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Going the Distance for Protein Function Prediction: A New Distance Metric for Protein Interaction Networks

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The oncologic burden of hepatitis C virus infection: A clinical perspective

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The Exceptional Oncogenicity of HTLV-1

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1186/s13059-021-02504-xopenalex-snapshot

Network propagation-based prioritization of long tail genes in 17 cancer types

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