ArticleHuman mutation2016
mutation3D: Cancer Gene Prediction Through Atomic Clustering of Coding Variants in the Structural Proteome.
Article in Human mutation, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.
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Who cites it
68 citing papers in PubMed.
- The structural context of mutations in proteins predicts their effect on antibiotic resistance.eLife · 2026Article
- Integrated Structural and Dynamic Analysis Reveals Destabilizing Effects of KRAS Missense Variants Associated with Lung Cancer.The protein journal · 2026Article
- Genomic landscape of drug binding and pharmacogenetic variation across diverse populations using SNPdrug3D.Nature communications · 2026Article
- A comprehensive in silico investigation into the deleterious nonsynonymous single nucleotide polymorphisms of the human transcription factor EB (TFEB) gene and their predicted association with cancer.Journal, genetic engineering & biotechnology · 2026Article
- Computational analysis of the structural and functional impact of the deleterious nsSNPs in the humanBiochemistry and biophysics reports · 2026Article
- Comprehensive analysis of the deleterious nonsynonymous, non-coding SNPs and cancer variants of human aldo-keto reductase type 1 (AKR1C1) protein and their probable association with disease risk and progression: a computational study.Biochemistry and biophysics reports · 2026Article
- Article
- Modeling the Effects of Single Nucleotide Polymorphisms (SNPs) on the Structure and Function of the HumanHuman mutation · 2026Article
- In silico functional, structural, and pathogenicity assessment of single nucleotide polymorphisms in the human SOX9 gene.Scientific reports · 2025Article
- Comprehensive in silico characterization of nonsynonymous SNPs in the human ezrin (EZR) gene and their role in disease pathogenesis.Biochemistry and biophysics reports · 2025Article
- Article
- A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology.Nature communications · 2025Article
- Computational investigation unveils pathogenic LIG3 non-synonymous mutations and therapeutic targets in acute myeloid leukemia.PloS one · 2025Article
- Protein structural context of cancer mutations reveals molecular mechanisms and candidate driver genes.Cell reports · 2024Article
- Bioinformatic Characterization of the Functional and Structural Effect of Single Nucleotide Mutations in Patients with High-Grade Glioma.Biomedicines · 2024Article
- Article
- A multiscale functional map of somatic mutations in cancer integrating protein structure and network topology.bioRxiv : the preprint server for biology · 2024Article
- Prediction of the most deleterious non-synonymous SNPs in the human IL1B gene: evidence from bioinformatics analyses.BMC genomic data · 2024Article
- A computational approach for structural and functional analyses of disease-associated mutations in the human CYLD gene.Genomics & informatics · 2024Article
- In silico functional, structural and pathogenicity analysis of missense single nucleotide polymorphisms in human MCM6 gene.Scientific reports · 2024Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
A new algorithm and Web server, mutation3D (http://mutation3d.org), proposes driver genes in cancer by identifying clusters of amino acid substitutions within tertiary protein structures. We demonstrate the feasibility of using a 3D clustering approach to implicate proteins in cancer based on explorations of single proteins using the mutation3D Web interface. On a large scale, we show that clustering with mutation3D is able to separate functional from nonfunctional mutations by analyzing a combination of 8,869 known inherited disease mutations and 2,004 SNPs overlaid together upon the same sets of crystal structures and homology models. Further, we present a systematic analysis of whole-genome and whole-exome cancer datasets to demonstrate that mutation3D identifies many known cancer genes as well as previously underexplored target genes. The mutation3D Web interface allows users to analyze their own mutation data in a variety of popular formats and provides seamless access to explore mutation clusters derived from over 975,000 somatic mutations reported by 6,811 cancer sequencing studies. The mutation3D Web interface is freely available with all major browsers supported.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.