Article

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

2020-12-01

Abstract excerpt

<title>Abstract</title> <p><bold>Background</bold>Today, there are a lot of markers on the prognosis and diagnosis of complex diseases such as primary breast cancer. However, our understanding of the drivers that influence cancer aggression is limited.<bold>Methods</bold>In this work, we study somatic mutation data consists of 450 metastatic breast tumor samples from cBio Cancer Genomics Portal. We use four softw...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: edba4a37-5295-5c85-ac80-a56311b24958
DOI: 10.21203/rs.3.rs-113748/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancerDOI 10.21203/rs.3.rs-113748/v1Read

EARN: An Ensemble Machine Learning Algorithm to Predict Driver Genes in Metastatic Breast CancerSemantic proximity Read

EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer.Semantic proximity Read

Evaluation and integration of cancer gene classifiers: identification and ranking of plausible drivers.Semantic proximity Read

BRDriver: Breast Cancer Driver Gene PredictorSemantic proximity Read

Gene Expression Assay: A New Panel for Early Metastatic Risk Estimation for Breast CancerSemantic proximity Read

CDMPred: A Tool for Predicting Cancer Driver Mutations with High-Quality Passenger Mutations and Ensemble LearningSemantic proximity Read

Machine learning techniques for identification of carcinogenic mutations, which cause breast adenocarcinoma.Semantic proximity Read

maGENEgerZ: An Efficient AI-Based Framework Can Extract More Expressed Genes and Biological Insights Underlying Breast Cancer Drug Response MechanismSemantic proximity Read

K-RAS Associated Gene-Mutation-Based Algorithm for Prediction of Treatment Response of Patients with Subtypes of Breast Cancer and Especially Triple-Negative CancerSemantic proximity Read

Genomic Machine Learning Model Predicts Radiation Therapy Benefit in Early-Stage Breast Cancer Patients with High AccuracySemantic proximity Read

An Ensemble-Base Machine Learning Approach to Predict 2- and 10-Year Breast CancerSemantic proximity Read

Novel Gene Signatures Predicting Breast Cancer Based on Random Forest and Artificial Neural NetworkSemantic proximity Read