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Distinguishing the rare "driver" mutations that fuel cancer progression from the vast background of "passenger" mutations in the non-coding genome is a fundamental challenge in cancer biology. A primary mechanism that non-coding driver…

Genomics · Quantitative Biology 2025-10-01 David Laub , Ethan Armand , Arda Pekis , Zekai Chen , Irsyad Adam , Shaun Porwal , Bing Ren , Kevin Brown , Hannah Carter

Advancing the discovery of prognostic cancer biomarkers is crucial for comprehending disease mechanisms, refining treatment plans, and improving patient outcomes. This study introduces Weighted Gene Topological Data Analysis (WGTDA), an…

Quantitative Methods · Quantitative Biology 2024-02-15 Ndivhuwo Nyase , Lebohang Mashatola , Aviwe Kohlakala , Kahn Rhrissorrakrai , Stephanie Muller

Lung cancer is a condition where there is abnormal growth of malignant cells that spread in an uncontrollable fashion in the lungs. Some common treatment strategies are surgery, chemotherapy, and radiation which aren't the best options due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-18 Ann Rachel , Pranav M Pawar , Mithun Mukharjee , Raja M , Tojo Mathew

Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC). However, in the clinic, molecular profiling is…

Computer Vision and Pattern Recognition · Computer Science 2023-05-09 Raktim Kumar Mondol , Ewan K. A. Millar , Peter H Graham , Lois Browne , Arcot Sowmya , Erik Meijering

Extracting genetic information from a full range of sequencing data is important for understanding diseases. We propose a novel method to effectively explore the landscape of genetic mutations and aggregate them to predict cancer type. We…

Genomics · Quantitative Biology 2018-10-10 Zexian Zeng , Andy Vo , Chengsheng Mao , Susan E Clare , Seema A Khan , Yuan Luo

An endogenous molecular-cellular network for both normal and abnormal functions is assumed to exist. This endogenous network forms a nonlinear stochastic dynamical system, with many stable attractors in its functional landscape. Normal or…

Subcellular Processes · Quantitative Biology 2007-09-06 P. Ao , D. Galas , L. Hood , X. -M. Zhu

Motivation: The consistent amount of different types of omics data requires novel methods of analysis and data integration. In this work we describe Regression2Net, a computational approach to analyse gene expression and methylation…

Computational Engineering, Finance, and Science · Computer Science 2015-07-06 Francesco Gadaleta , Kyrylo Bessonov

Cancer is a heterogeneous disease with diverse molecular etiologies and outcomes. The Cancer Genome Atlas (TCGA) has released a large compendium of over 10,000 tumors with RNA-seq gene expression measurements. Gene expression captures the…

Genomics · Quantitative Biology 2017-11-15 Gregory P. Way , Casey S. Greene

In cancer research, profiling studies have been extensively conducted, searching for genes/SNPs associated with prognosis. Cancer is a heterogeneous disease. Examining similarity and difference in the genetic basis of multiple subtypes of…

Methodology · Statistics 2013-04-18 Jin Liu , Jian Huang , Yawei Zhang , Qing Lan , Nathaniel Rothman , Tongzhang Zheng , Shuangge Ma

BACKGROUND: Breast cancer has emerged as one of the most prevalent cancers among women leading to a high mortality rate. Due to the heterogeneous nature of breast cancer, there is a need to identify differentially expressed genes associated…

Machine Learning · Computer Science 2021-11-30 Sheetal Rajpal , Ankit Rajpal , Manoj Agarwal , Naveen Kumar

m5C modification is a type of RNA methylation modification, and its major methyltransferase, NSUN2, catalyzes m5C modification. NSUN2 is overexpressed in a variety of cancers, and it affects the metabolism of RNA from target genes by…

Biomolecules · Quantitative Biology 2025-06-10 Zifang He , Longtao Yang , Peiyao Ma

Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with trait diversity and disease susceptibility, yet the functional properties of many genetic variants and their molecular…

Genomics · Quantitative Biology 2018-03-21 Gary Wilk , Rosemary Braun

The application of machine learning to transcriptomics data has led to significant advances in cancer research. However, the high dimensionality and complexity of RNA sequencing (RNA-seq) data pose significant challenges in pan-cancer…

Genomics · Quantitative Biology 2024-08-15 Jong Hyun Kim , Jongseong Jang

Cancer is a term that denotes a group of diseases caused by abnormal growth of cells that can spread in different parts of the body. According to the World Health Organization (WHO), cancer is the second major cause of death after…

Machine Learning · Computer Science 2023-01-31 Fadi Alharbi , Aleksandar Vakanski

Recent breakthroughs in cancer research have come via the up-and-coming field of pathway analysis. By applying statistical methods to prior known gene and protein regulatory information, pathway analysis provides a meaningful way to…

Genomics · Quantitative Biology 2017-10-11 Yue Zhao

We propose a methodology for the identification of transcription factors involved in the deregulation of genes in tumoral cells. This strategy is based on the inference of a reference gene regulatory network that connects transcription…

Molecular Networks · Quantitative Biology 2020-04-20 Magali Champion , Julien Chiquet , Pierre Neuvial , Mohamed Elati , François Radvanyi , Etienne Birmelé

Cancers are mainly caused by somatic genomic alterations (SGAs) that perturb cellular signaling systems and eventually activate oncogenic processes. Therefore, understanding the functional impact of SGAs is a fundamental task in cancer…

Molecular Networks · Quantitative Biology 2019-09-24 Yifeng Tao , Chunhui Cai , William W. Cohen , Xinghua Lu

Bioinformatics tools have been developed to interpret gene expression data at the gene set level, and these gene set based analyses improve the biologists' capability to discover functional relevance of their experiment design. While…

Machine Learning · Statistics 2019-01-01 Hung-I Harry Chen , Yu-Chiao Chiu , Tinghe Zhang , Songyao Zhang , Yufei Huang , Yidong Chen

In this paper we propose network methodology to infer prognostic cancer biomarkers based on the epigenetic pattern DNA methylation. Epigenetic processes such as DNA methylation reflect environmental risk factors, and are increasingly…

Applications · Statistics 2016-08-02 Thomas E. Bartlett , Alexey Zaikin

Cancer is one of the leading causes of human death. Many efforts have made to understand its mechanism and have further identified many proteins and DNA sequence variations as suspected targets for therapy. However, drugs targeting these…

Genomics · Quantitative Biology 2019-10-10 Anyou Wang , Hai Rong