Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

From driver genes to gene families: A computational analysis of oncogenic mutations and ubiquitination anomalies in hepatocellular carcinoma.

Computational biology and chemistry - 1 Oct 2024

Wang Meng, Yan Xinyue, Dong Yanan, Li Xiaoqin, Gao Bin

Abstract excerpt

Hepatocellular carcinoma (HCC) is a widespread primary liver cancer with a high fatality rate. Despite several genes with oncogenic effects in HCC have been identified, many remain undiscovered. In this study, we conducted a comprehensive computational analysis to explore the involvement of genes within the same families as known driver genes in HCC. Specifically, we expanded the concept beyond single-gene...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Carcinoma, Hepatocellular
Share to Computational Biology

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Liver Neoplasms

Share to Mutation

Share to Oncogenes

Share to Ubiquitination

Source

Identifiers

PMID: 38852361
DOI: 10.1016/j.compbiolchem.2024.108119

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

From driver genes to gene families: A computational analysis of oncogenic mutations and ubiquitination anomalies in hepatocellular carcinoma.PMID 38852361Read ↗

Machine learning and multi-omics data reveal driver gene-based molecular subtypes in hepatocellular carcinoma for precision treatment.Semantic proximity Read ↗

Identification of driver genes and target drugs-related genes in liver cancer based on targeted next generation sequencing.Semantic proximity Read ↗

Identification of drivers from cancer genome diversity in hepatocellular carcinoma.Semantic proximity Read ↗

The mutational landscape of hepatocellular carcinoma.Semantic proximity Read ↗

Advances in genomic hepatocellular carcinoma researchSemantic proximity Read ↗

Integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma.Semantic proximity Read ↗

Genomic analysis of liver cancer unveils novel driver genes and distinct prognostic features.Semantic proximity Read ↗

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer TypesSemantic proximity Read ↗

PANoptosis-based molecular subtyping and HPAN-index predicts therapeutic response and survival in hepatocellular carcinomaSemantic proximity Read ↗

Molecular genomic landscapes of hepatobiliary cancer.Semantic proximity Read ↗

Multi-modal meta-analysis of 1494 hepatocellular carcinoma samples reveals vast impacts of consensus driver genes on phenotypesSemantic proximity Read ↗

Deciphering the Molecular Complexity of Hepatocellular Carcinoma: Unveiling Novel Biomarkers and Therapeutic Targets Through Advanced Bioinformatics AnalysisSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.