A Novel Approach to Evaluating Cancer Driver Gene Mutation ...

Individualized discovery of rare cancer drivers in global network ...

Method NEAdriver employs knowledge from global networks to predict novel cancer driver genes in an individualized manner, which is done by ...

ConsensusDriver Improves upon Individual Algorithms for Predicting ...

These findings assess state-of-the-art cancer driver prediction methods and develop a new and improved consensus-based approach for use in precision.

Evaluating the evaluation of cancer driver genes | Request PDF

Significance Modern large-scale sequencing of human cancers seeks to comprehensively discover mutated genes that confer a selective advantage to cancer ...

A Novel Approach to Detect Programed Death Ligand 1 (PD-L1 ...

Multiple biomarkers are under evaluation to guide the use of immune checkpoint inhibitors in non–small-cell lung cancer (NSCLC), ...

Evaluating the evaluation of cancer driver genes - SUNY New Paltz

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge.

A Novel Machine Learning Method for Mutational Analysis to ... - OUCI

We investigated the function of the potential driver genes and related pathways. By presenting lower-frequency genes, we recognized breast cancer-related ...

Evaluating the evaluation of cancer driver genes

Sequencing has identified millions of somatic mutations in human cancers, but distinguishing cancer driver genes remains a major challenge.

Evaluation of a novel approach to circulating tumor cell isolation for ...

Cancer gene panel analysis ... Genomic mutations were analyzed using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (Thermo Fisher Scientific, Inc.), a ...

Computational methods for cancer driver discovery: A survey

MutSigCV [13] is a method to discover cancer drivers by assessing the significance of mutations in genes. Cancer drivers predicted by MutSigCV are mutated more ...

(PDF) Novel ratio-metric features enable the identification of new ...

This study defines new features and builds a pan-cancer model, cTaG, to identify new driver genes. The features capture the functional impact of the mutations ...

A novel hypergraph model for identifying and prioritizing ... - PLOS

Cancer development is driven by an accumulation of a small number of driver genetic mutations that confer the selective growth advantage to the cell, ...

New approach to cancer therapy based on a molecularly defined ...

Driver Mutations Determining Response to Treatment ... Despite tumoral complexity, increased knowledge about the molecular characteristics of ...

Characterization of potential driver mutations involved in human ...

Among the aforementioned known breast cancer driver genes, a tumor suppressor (TSG), TP53, is the top-mutated gene, with nearly 100% risk of ...

Module Analysis Captures Pancancer Genetically and ... - The Lancet

We present an algorithm that combines multiple sources of molecular data to identify novel genes that are involved in cancer development.

TOPDRIVER: the novel identifier of cancer driver genes in Gastric ...

By this method, we detect driver genes as the one that either have a high burden of driver mutations or include mutations that have a higher ...

Prioritizing Cancer Genes Based on an Improved Random Walk ...

Identifying driver genes that contribute to cancer progression from numerous passenger genes, although a central goal, is a major challenge. The ...

Novel Approaches in Ovarian Cancer Research against ... - MDPI

Whole-genome and whole-exome sequencing allow for the investigation of somatic mutations related to cancer. Additionally, the use of RNA ...

Prediction of cancer driver genes through network-based moment ...

However, those analy- ses are complicated by the extensive mutational heterogeneity: Many genes are mutated in a small number of samples, and only few genes ...

A Novel Approach to Quantify Heterogeneity of Intrahepatic ...

Intrahepatic cholangiocarcinoma (IHC) is a heterogeneous tumor. The hidden-genome classifier, a supervised machine learning–based algorithm, was ...

Characterization of driver mutations in Chinese non-small cell lung ...

It is important to design a clinically cost-effective gene panel, which contains most important genes closely related to cancer treatment and ...