ArticleBMC genomics2015
ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers.
Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Cell-free DNA Methylation as a Predictive Biomarker of Response to Neoadjuvant Chemotherapy for Patients with Muscle-invasive Bladder Cancer in SWOG S1314.European urology oncology · 2023Trial
- Smart Biosensor for Breast Cancer Survival Prediction Based on Multi-View Multi-Way Graph Learning.Sensors (Basel, Switzerland) · 2024Article
- Improving the robustness and stability of a machine learning model for breast cancer prognosis through the use of multi-modal classifiers.Scientific reports · 2023Article
- Construction and validation of an aging-related gene signature for prognosis prediction of patients with breast cancer.Cancer reports (Hoboken, N.J.) · 2023Article
- Identification of a gene expression signature associated with breast cancer survival and risk that improves clinical genomic platforms.Bioinformatics advances · 2023Article
- Joint learning sample similarity and correlation representation for cancer survival prediction.BMC bioinformatics · 2022Article
- A network-based approach to identify expression modules underlying rejection in pediatric liver transplantation.Cell reports. Medicine · 2022Article
- Article
- Integrative network analysis of early-stage lung adenocarcinoma identifies aurora kinase inhibition as interceptor of invasion and progression.Nature communications · 2022Article
- Stacking Machine Learning Algorithms for Biomarker-Based Preoperative Diagnosis of a Pelvic Mass.Cancers · 2022Article
- Data analysis methods for defining biomarkers from omics data.Analytical and bioanalytical chemistry · 2022Review
- Prediction of lung cancer immunotherapy response via machine learning analysis of immune cell lineage and surface markers.Cancer biomarkers : section A of Disease markers · 2022Article
- Evaluation of the added value of viral genomic information for predicting severity of influenza infection.BMC infectious diseases · 2021Article
- Changes in pregnancy-related serum biomarkers early in gestation are associated with later development of preeclampsia.PloS one · 2020Article
- Effect of dietary fat and sucrose consumption on cardiac fibrosis in mice and rhesus monkeys.JCI insight · 2019Article
- Latent Model-Based Clustering for Biological Discovery.iScience · 2019Article
- Reprogramming of regulatory network using expression uncovers sex-specific gene regulation in Drosophila.Nature communications · 2018Article
- A network medicine approach to build a comprehensive atlas for the prognosis of human cancer.Briefings in bioinformatics · 2016Article
- Regularized logistic regression with network-based pairwise interaction for biomarker identification in breast cancer.BMC bioinformatics · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundWith the explosion of genomic data over the last decade, there has been a tremendous amount of effort to understand the molecular basis of cancer using informatics approaches. However, this has proven to be extremely difficult primarily because of the varied etiology and vast genetic heterogeneity of different cancers and even within the same cancer. One particularly challenging problem is to predict prognostic outcome of the disease for different patients.
resultsHere, we present ENCAPP, an elastic-net-based approach that combines the reference human protein interactome network with gene expression data to accurately predict prognosis for different human cancers. Our method identifies functional modules that are differentially expressed between patients with good and bad prognosis and uses these to fit a regression model that can be used to predict prognosis for breast, colon, rectal, and ovarian cancers. Using this model, ENCAPP can also identify prognostic biomarkers with a high degree of confidence, which can be used to generate downstream mechanistic and therapeutic insights.
conclusionENCAPP is a robust method that can accurately predict prognostic outcome and identify biomarkers for different human cancers.
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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.