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Inhibiting a signalling pathway concerns controlling the cellular processes of a cancer cell's viability, cell division, and death. Assay protocols created to see if the molecular structures of the drugs being tested have the desired…

Quantitative Methods · Quantitative Biology 2022-07-19 Roumen Anguelov , G Manjunath , Avulundiah E Phiri , Trevor T Nyakudya , Priyesh Bipath , June C Serem , Yvette N Hlophe

A major challenge for cancer pathologists is to determine whether a new tumor in a patient with cancer is a metastasis or an independent occurrence of the disease. In recent years numerous studies have evaluated pairs of tumor specimens to…

Applications · Statistics 2015-11-18 Irina Ostrovnaya , Venkatraman E. Seshan , Colin B. Begg

DNA microarrays are a relatively new technology that can simultaneously measure the expression level of thousands of genes. They have become an important tool for a wide variety of biological experiments. One of the most common goals of DNA…

Methodology · Statistics 2013-07-02 Eric Bair

DNA microarray gene-expression data has been widely used to identify cancerous gene signatures. Microarray can increase the accuracy of cancer diagnosis and prognosis. However, analyzing the large amount of gene expression data from…

Neural and Evolutionary Computing · Computer Science 2024-11-21 Maryam Eshraghi Evari , Md Nasir Sulaiman , Amir Rajabi Behjat

Data augmentation refers to a group of techniques whose goal is to battle limited amount of available data to improve model generalization and push sample distribution toward the true distribution. While different augmentation strategies…

Quantitative Methods · Quantitative Biology 2020-06-03 Ruqian Hao , Khashayar Namdar , Lin Liu , Masoom A. Haider , Farzad Khalvati

In Cowell et al. (2007), a Bayesian network for analysis of mixed traces of DNA was presented using gamma distributions for modelling peak sizes in the electropherogram. It was demonstrated that the analysis was sensitive to the choice of a…

Methodology · Statistics 2013-06-21 Therese Graversen , Steffen Lauritzen

Significant advances in biotechnology have allowed for simultaneous measurement of molecular data points across multiple genomic and transcriptomic levels from a single tumor/cancer sample. This has motivated systematic approaches to…

The research reported in this paper identifies the epigenetic biomarker (methylation beta pattern) of breast cancer. Many cancers are triggered by abnormal gene expression levels caused by aberrant methylation of CpG sites in the DNA. In…

Genomics · Quantitative Biology 2019-10-16 Maxim Vaysburd

Identifying disease-associated changes in DNA methylation can help to gain a better understanding of disease etiology. Bisulfite sequencing technology allows the generation of methylation profiles at single base of DNA. We previously…

Identifying important biomarkers that are predictive for cancer patients' prognosis is key in gaining better insights into the biological influences on the disease and has become a critical component of precision medicine. The emergence of…

Methodology · Statistics 2016-03-22 Hyokyoung Grace Hong , Jian Kang , Yi Li

Sensitive and reliable methylation assay is important for oncogentic studies and clinical applications. Here, a new methylation assay was developed by the use of adapter-dependent adapter in library preparation. This new assay avoids the…

Biomolecules · Quantitative Biology 2024-10-08 Jia Zhang , Peng Qi , Li Xiao , Mengxi Yuan , Jun Chuan , Yaling Zeng , Li-mei Lin , Yue Gu , Yan Zhang , Duan-fang Liao , Kai Li

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

Use of next-generation sequencing technologies to transcriptomics (RNA-seq) for gene expression profiling has found widespread application in studying different biological conditions including cancers. However, RNA-seq experiments are still…

Methodology · Statistics 2022-08-08 Birbal Prasad , Xinzhong Li

Predictive modeling of the evolutionary dynamics of cancer is a challenge issue in computational cancer biology. In this paper, we propose a general mathematical model framework for the evolutionary dynamics of cancer with plasticity and…

Cell Behavior · Quantitative Biology 2020-01-10 Jinzhi Lei

Predicting drug responses using genetic and transcriptomic features is crucial for enhancing personalized medicine. In this study, we implemented an ensemble of machine learning algorithms to analyze the correlation between genetic and…

Genomics · Quantitative Biology 2025-07-04 Johannes Schlüter , Alexander Schönhuth

Meta-analysis of multiple genome-wide association studies (GWAS) is effective for detecting single or multi marker associations with complex traits. We develop a flexible procedure ("STAMP") based on mixture models to perform region based…

Methodology · Statistics 2018-01-01 Andriy Derkach , Ruth M. Pfeiffer

Nowadays, the screening methods for the early detection of lung cancer struggle with several limitations such as many false positive results and low sensitivity. The detection of specific biomarkers is of high interest to complement these…

Quantitative Methods · Quantitative Biology 2021-02-19 Juul Goossens , Jente Gieghase , Elien Derveaux , Peter Adriaensens

In recent years, cancer genome sequencing and other high-throughput studies of cancer genomes have generated many notable discoveries. In this review, Novel genomic alteration mechanisms, such as chromothripsis (chromosomal crisis) and…

Genomics · Quantitative Biology 2014-09-12 Edwin Wang

Cervical cancer, the fourth leading cause of cancer in women globally, requires early detection through Pap smear tests to identify precancerous changes and prevent disease progression. In this study, we performed a focused analysis by…

Image and Video Processing · Electrical Eng. & Systems 2025-05-22 Abdul Samad Shaik , Shashaank Mattur Aswatha , Rahul Jashvantbhai Pandya

Machine learning models for medical image analysis often suffer from poor performance on important subsets of a population that are not identified during training or testing. For example, overall performance of a cancer detection model may…

Machine Learning · Computer Science 2019-11-18 Luke Oakden-Rayner , Jared Dunnmon , Gustavo Carneiro , Christopher Ré