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Background: It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of "driver" mutations that are…

Genomics · Quantitative Biology 2013-07-16 Gregory Ryslik , Yuwei Cheng , Kei-Hoi Cheung , Yorgo Modis , Hongyu Zhao

The genomic profile underlying an individual tumor can be highly informative in the creation of a personalized cancer treatment strategy for a given patient; a practice known as precision oncology. This involves next generation sequencing…

Computer-aided tumor detection has shown great potential in enhancing the interpretation of over 80 million CT scans performed annually in the United States. However, challenges arise due to the rarity of CT scans with tumors, especially…

Image and Video Processing · Electrical Eng. & Systems 2024-09-11 Qi Chen , Yuxiang Lai , Xiaoxi Chen , Qixin Hu , Alan Yuille , Zongwei Zhou

The purpose of cancer genome sequencing studies is to determine the nature and types of alterations present in a typical cancer and to discover genes mutated at high frequencies. In this article we discuss statistical methods for the…

Applications · Statistics 2011-07-26 Lorenzo Trippa , Giovanni Parmigiani

A central goal in cancer genomics is to identify the somatic alterations that underpin tumor initiation and progression. This task is challenging as the mutational profiles of cancer genomes exhibit vast heterogeneity, with many alterations…

Genomics · Quantitative Biology 2017-04-28 Borislav H. Hristov , Mona Singh

Motivation. Understanding the pan-cancer mutational landscape offers critical insights into the molecular mechanisms underlying tumorigenesis. While patient-level machine learning techniques have been widely employed to identify tumor…

Machine Learning · Computer Science 2025-08-29 Yifan Dou , Adam Khadre , Ruben C Petreaca , Golrokh Mirzaei

Comparing large covariance matrices has important applications in modern genomics, where scientists are often interested in understanding whether relationships (e.g., dependencies or co-regulations) among a large number of genes vary…

Methodology · Statistics 2017-04-04 Jinyuan Chang , Wen Zhou , Wen-Xin Zhou , Lan Wang

High-throughput genetic and epigenetic data are often screened for associations with an observed phenotype. For example, one may wish to test hundreds of thousands of genetic variants, or DNA methylation sites, for an association with…

Methodology · Statistics 2017-10-20 Eric F. Lock , David B. Dunson

Cancer development is associated with aberrant DNA methylation, including increased stochastic variability. Statistical tests for discovering cancer methylation biomarkers have focused on changes in mean methylation. To improve the power of…

Methodology · Statistics 2023-06-27 James Y. Dai , Heng Chen , Xiaoyu Wang , Wei Sun , Ying Huang , William M. Grady , Ziding Feng

There are numerous stochastic models for cancer risk for a given tissue. Many rely on the following two hypotheses. 1. There is a fixed probability that a given cell division will eventually lead to a cancerous cell. 2. Cell divisions are…

Tissues and Organs · Quantitative Biology 2015-08-20 Rinaldo B. Schinazi

Co-change candidates are the group of code fragments that require a change if any of these fragments experience a modification in a commit operation during software evolution. The cloned co-change candidates are a subset of the co-change…

Software Engineering · Computer Science 2025-02-21 Md Nadim , Manishankar Mondal , Chanchal K. Roy , Kevin Schneider

Statistical inference on the cancer-site specificities of collective ultra-rare whole genome somatic mutations is an open problem. Traditional statistical methods cannot handle whole-genome mutation data due to their…

Methodology · Statistics 2023-01-02 Saptarshi Chakraborty , Zoe Guan , Colin B. Begg , Ronglai Shen

Mathematical oncology is a rapidly evolving interdisciplinary field that uses mathematical models to enhance our understanding of cancer dynamics, including tumor growth, metastasis, and treatment response. Tumor-immune interactions play a…

Quantitative Methods · Quantitative Biology 2025-11-05 Chenghang Li , Jinzhi Lei

Background. A large number of algorithms is being developed to reconstruct evolutionary models of individual tumours from genome sequencing data. Most methods can analyze multiple samples collected either through bulk multi-region…

Genomics · Quantitative Biology 2019-03-26 Daniele Ramazzotti , Alex Graudenzi , Luca De Sano , Marco Antoniotti , Giulio Caravagna

The problem of the onset and growth of solid tumour in homogeneous tissue is regarded using an approach based on local interaction between the tumoral and the sane tissue cells. The characteristic sizes and growth rates of spherical…

Cell Behavior · Quantitative Biology 2007-05-23 R. G. Khlebopros , V. A. Slepkov , V. G. Sukhovolsky , Y. V. Mironov , V. E. Fedorov , S. P. Gabuda

Explicit accounting for copy number alterations can dramatically improve mutation frequency estimates, leading to more accurate phylogeny reconstructions and subclone characterizations.

Cancer genomes exhibit a large number of different alterations that affect many genes in a diverse manner. It is widely believed that these alterations follow combinatorial patterns that have a strong connection with the underlying…

Machine Learning · Computer Science 2016-01-26 Jack P. Hou , Amin Emad , Gregory J. Puleo , Jian Ma , Olgica Milenkovic

Background: Regions with copy number variations (in germline cells) or copy number alteration (in somatic cells) are of great interest for human disease gene mapping and cancer studies. They represent a new type of mutation and are…

Genomics · Quantitative Biology 2012-05-07 Wentian Li , Annette Lee , Peter K Gregersen

Cancer is a heterogeneous disease with different combinations of genetic and epigenetic alterations driving the development of cancer in different individuals. While these alterations are believed to converge on genes in key cellular…

Quantitative Methods · Quantitative Biology 2015-03-31 Mark D. M. Leiserson , Hsin-Ta Wu , Fabio Vandin , Benjamin J. Raphael

The fitness of somatic cells of metazoan, the ability of proliferation and survival, depends on microenvironment. In somatic evolution, a mutated cell in a tissue clonally expands abnormally because of its high fitness as normal cells in a…

Populations and Evolution · Quantitative Biology 2015-09-07 Xiang-Ping Jia , Hong Sun