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Identifying the mutations that drive cancer growth is key in clinical decision making and precision oncology. As driver mutations confer selective advantage and thus have an increased likelihood of occurrence, frequency-based statistical…

Genomics · Quantitative Biology 2021-05-04 Adnan Akbar , Andrey Solovyev , John W Cassidy , Nirmesh Patel , Harry W Clifford

The accumulation of somatic mutations is a driver of cancer and has long been associated with ageing. Due to limitations in quantifying mutation burden with age in non-cancerous tissues, the impact of somatic mutations in other ageing…

Genomics · Quantitative Biology 2023-07-31 Kasit Chatsirisupachai , João Pedro de Magalhães

Cancer development is driven by mutations and selective forces, including the action of the immune system and interspecific competition. When administered to patients, anti-cancer therapies affect the development and dynamics of tumours,…

Dynamical Systems · Mathematics 2021-09-30 Elena Piretto , Marcello Delitala , Peter S. Kim , Federico Frascoli

In cancer genomics, it is of great importance to distinguish driver mutations, which contribute to cancer progression, from causally neutral passenger mutations. We propose a random-effect regression approach to estimate the effects of…

Methodology · Statistics 2023-06-30 Kin Yau Wong , Donglin Zeng , D. Y. Lin

Metastasis, the spread of cancer cells from a primary tumor to secondary location(s) in the human organism, is the ultimate cause of death for the majority of cancer patients. That is why, it is crucial to understand metastases evolution in…

Populations and Evolution · Quantitative Biology 2020-06-24 Maroussia Slavtchova-Bojkova , Kaloyan Vitanov

Genomic aberrations, such as somatic copy number alterations, are frequently observed in tumor tissue. Recurrent aberrations, occurring in the same region across multiple subjects, are of interest because they may highlight genes associated…

Statistics Theory · Mathematics 2014-03-11 Vonn Walter , Fred A. Wright , Andrew B. Nobel

Accurate prediction of cancer progression remains a challenge due to the high heterogeneity of molecular omics data across patients. While biologically informed models have improved the interpretability of these predictions, a persistent…

Machine Learning · Computer Science 2026-04-21 Koushik Howlader , Md Tauhidul Islam , Wei Le

In this thesis we develop minimal models of the relationship between motility, growth, and evolution of cancer cells. We utilise simple simulations of a population of individual cells in space to examine how changes in mechanical properties…

Populations and Evolution · Quantitative Biology 2020-05-20 Chay Paterson

We study the effect of intratumor heterogeneity in the likelihood of cancer cells moving from a primary tumor to other sites in the human body, generating a metastatic process. We model different scenarios of competition between tumor cells…

Populations and Evolution · Quantitative Biology 2025-10-28 André Rocha , Claudia Manini , José I López , Annick Laruelle

We present a general computational theory of cancer and its developmental dynamics. The theory is based on a theory of the architecture and function of developmental control networks which guide the formation of multicellular organisms.…

Molecular Networks · Quantitative Biology 2011-11-16 Eric Werner

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

One of the important issues in oncology is finding the genes that perturbation the cell functionality, and result in cancer propagation. The genes, namely driver genes, when they mutate in expression, result in cancer through activation of…

Molecular Networks · Quantitative Biology 2020-12-16 Mostafa Akhavansafar , Babak Teimourpour

The dynamics of tumour evolution are not well understood. In this paper we provide a statistical framework for evaluating the molecular variation observed in different parts of a colorectal tumour. A multi-sample version of the Ewens…

Populations and Evolution · Quantitative Biology 2010-04-26 A. D. Barbour , Simon Tavaré

Next-generation sequencing technologies allow the measurement of somatic mutations in a large number of patients from the same cancer type. One of the main goals in analyzing these mutations is the identification of mutations associated…

Quantitative Methods · Quantitative Biology 2016-09-13 Tommy Hansen , Fabio Vandin

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

Heterogeneity within tumour cell populations is associated with an increase in malignancy and appears to play an important role during cancer metastasis. Using in silico experiments, we study the interplay between collective behaviours and…

Tissues and Organs · Quantitative Biology 2015-01-05 Adrien Hallou , Joel Jennings , Alexandre Kabla

Cancer progression is an evolutionary process that is driven by mutation and selection in a population of tumor cells. We discuss mathematical models of cancer progression, starting from traditional multistage theory. Each stage is…

Populations and Evolution · Quantitative Biology 2011-08-31 Moritz Gerstung , Niko Beerenwinkel

Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating…

Genomics · Quantitative Biology 2017-01-02 Junhua Zhang , Shihua Zhang

While we once thought of cancer as single monolithic diseases affecting a specific organ site, we now understand that there are many subtypes of cancer defined by unique patterns of gene mutations. These gene mutational data, which can be…

Quantitative Methods · Quantitative Biology 2017-03-07 Jipeng Qiang , Wei Ding , John Quackenbush , Ping Chen

Recent studies of cancer somatic mutation profiles seek to identify mutations for targeted therapy in personalized medicine. Analysis of profiles, however, is not trivial, as each profile is heterogeneous and there are multiple confounding…

Machine Learning · Statistics 2020-05-25 Rahul Mehta , Muge Karaman