ReviewNature reviews. Genetics2017
Functional variomics and network perturbation: connecting genotype to phenotype in cancer.
Review in Nature reviews. Genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
64 citing papers in PubMed, 105 citations in OpenAlex.
- MKLNID: Identifying Melanoma-related Pathogenic Genes Through Multiple Kernel Learning and Network Impulsive Dynamics.Interdisciplinary sciences, computational life sciences · 2026Article
- eSIG-Net: an interaction language model that decodes the protein code of single mutations.Nature methods · 2026Article
- Lung cancer associated with cystic airspaces in the perioperative immunotherapy era: radiologic and pathologic pitfalls, surgical extent, and management implications.Translational lung cancer research · 2026Review
- Proteoform medicine: characterizing and targeting protein forms in human disease.Nature reviews. Genetics · 2026Review
- eSIG-Net: Accurate prediction of single-mutation induced perturbations on protein interactions using a language model.bioRxiv : the preprint server for biology · 2026Article
- Interactome mapping in human excitatory neurons reveals novel risk genes and pathways in Alzheimer's disease.bioRxiv : the preprint server for biology · 2026Article
- Predicting neuroblastoma prognosis using machine learning analysis of metabolism-related gene network perturbation.BMC pediatrics · 2026Article
- Integrated Bioinformatics Analysis of Differentially Expressed RNA-Binding Proteins in Human Gliomas.Cellular and molecular neurobiology · 2025Article
- Refining treatment strategies for non-small cell lung cancer lacking actionable mutations: insights from multi-omics studies.British journal of cancer · 2025Review
- Long noncoding RNAs in acute myeloid leukemia: biomarkers, prognostic indicators, and treatment potential.Cancer cell international · 2025Review
- CaMutQC: An R package for integrative quality control and filtration of cancer somatic mutations.Computational and structural biotechnology journal · 2025Article
- GREGoR: Accelerating Genomics for Rare Diseases.ArXiv · 2024Article
- Article
- Identification and validation of a novel predictive signature based on hepatocyte-specific genes in hepatocellular carcinoma by integrated analysis of single-cell and bulk RNA sequencing.BMC medical genomics · 2024Article
- Contributions of transcriptional noise to leukaemia evolution: KAT2A as a case-study.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Article
- Pan-cancer analysis of oncogenic role of insulin-like growth factor-binding proteins and validation in ovarian cancer.Cancer medicine · 2023Article
- Gain-of-Function Variomics and Multi-omics Network Biology for Precision Medicine.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Article
- Pan-cancer assessment of mutational landscape in intrinsically disordered hotspots reveals potential driver genes.Nucleic acids research · 2022Article
4 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Proteins interact with other macromolecules in complex cellular networks for signal transduction and biological function. In cancer, genetic aberrations have been traditionally thought to disrupt the entire gene function. It has been increasingly appreciated that each mutation of a gene could have a subtle but unique effect on protein function or network rewiring, contributing to diverse phenotypic consequences across cancer patient populations. In this Review, we discuss the current understanding of cancer genetic variants, including the broad spectrum of mutation classes and the wide range of mechanistic effects on gene function in the context of signalling networks. We highlight recent advances in computational and experimental strategies to study the diverse functional and phenotypic consequences of mutations at the base-pair resolution. Such information is crucial to understanding the complex pleiotropic effect of cancer genes and provides a possible link between genotype and phenotype in cancer.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.