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Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena,…

We consider integrative modeling of multiple gene networks and diverse genomic data, including protein-DNA binding, gene expression and DNA sequence data, to accurately identify the regulatory target genes of a transcription factor (TF).…

Applications · Statistics 2012-03-21 Peng Wei , Wei Pan

Gene regulation is one of the most important fundamental biological processes in living cells. It involves multiple protein molecules that locate specific sites on DNA and assemble gene initiation or gene repression multi-molecular…

Biological Physics · Physics 2019-10-23 Jaeoh Shin , Anatoly B. Kolomeisky

Although cancer is known to be characterized by several unifying biological hallmarks, systems biology has had limited success in identifying molecular signatures present in in all types of cancer. The current availability of rich data sets…

Motivation: Driver (epi)genomic alterations underlie the positive selection of cancer subpopulations, which promotes drug resistance and relapse. Even though substantial heterogeneity is witnessed in most cancer types, mutation accumulation…

Summary: Macromolecular assembly vertebrates essential cellular processes, such as gene regulation and signal transduction. A major challenge for conventional computational methods to study these processes is tackling the exponential…

Quantitative Methods · Quantitative Biology 2013-01-08 J. M. G. Vilar , L. Saiz

The recent advances in cancer immunotherapy boosted the development of tumor-immune system models aiming to provide mechanistic understanding and indicate more efficient treatment regimes. However, the complexity of such models, their…

Dynamical Systems · Mathematics 2023-09-18 Dimitrios G. Patsatzis

We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes: Gene A and Gene B which synthesize the TFs and the target gene proteins respectively. We show through analytic…

Quantitative Methods · Quantitative Biology 2009-11-13 Rajesh Karmakar , Indrani Bose

The interaction between proteins and nucleic acids is crucial for processes that sustain cellular function, including DNA maintenance and the regulation of gene expression and translation. Amino acid mutations in protein-nucleic acid…

Biomolecules · Quantitative Biology 2025-12-01 Somnath Mondal , Tinkal Mondal , Soumajit Pramanik , Rukmankesh Mehra

Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the most part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.).…

Quantitative Methods · Quantitative Biology 2009-05-08 Roberto Amato , Michele Pinelli , Daniel D'Andrea , Gennaro Miele , Mario Nicodemi , Giancarlo Raiconi , Sergio Cocozza

We present multiscale models of cancer tumor invasion with components at the molecular, cellular, and tissue levels. We provide biological justifications for the model components, present computational results from the model, and discuss…

Quantitative Methods · Quantitative Biology 2023-02-14 Bruce P. Ayati , Glenn F. Webb , Alexander R. A. Anderson

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

Recent works have stressed the important role that random mutations have in the development of cancer phenotype. We challenge this current view by means of bioinformatic data analysis and computational modelling approaches. Not all the…

Cell Behavior · Quantitative Biology 2017-06-28 Gianluca Ascolani , Pietro Lió

Signaling pathways are responsible for the regulation of cell processes, such as monitoring the external environment, transmitting information across membranes, and making cell fate decisions. Given the increasing amount of biological data…

Molecular Networks · Quantitative Biology 2020-04-07 Daniel Inostroza , Cecilia Hernández , Diego Seco , Gonzalo Navarro , Alvaro Olivera-Nappa

Principal component analysis (PCA) is a tool to capture factors that explain variation in data. Across domains, data are now collected across multiple contexts (for example, individuals with different diseases, cells of different types, or…

Machine Learning · Statistics 2026-01-22 Kexin Wang , Salil Bhate , João M. Pereira , Joe Kileel , Matylda Figlerowicz , Anna Seigal

One of the mechanisms that ensure cancer robustness is tumor heterogeneity, and its effects on tumor cells dynamics have to be taken into account when studying cancer progression. There is no unifying theoretical framework in mathematical…

Tissues and Organs · Quantitative Biology 2007-05-23 Georgy P. Karev , Artem S. Novozhilov , Eugene V. Koonin

Transcription factors (TFs) are key regulators of gene expression. Based on the classical scenario in which the TF search process switches between one-dimensional motion along the DNA molecule and free Brownian motion in the nucleus, we…

Genomics · Quantitative Biology 2010-10-15 Godefroy Malherbe , David Holcman

We investigate a new dynamical system that describes tumor-host interaction. The equation that describes the untreated tumor growth is based on non-extensive statistical mechanics. Recently, this model has been shown to fit successfully…

Responsible for many complex human diseases including cancers, disrupted or abnormal gene interactions can be identified through their expression changes correlating with the progression of a disease. However, the examination of all…

Quantitative Methods · Quantitative Biology 2013-02-18 Salim Chowdhury , Yanjun Qi , Alex Stewart , Rachel Ostroff , Renqiang Min

The standard methods for detecting differential gene expression are mostly designed for analyzing a single gene expression experiment. When data from multiple related gene expression studies are available, separately analyzing each study is…

Methodology · Statistics 2013-11-07 Yingying Wei , Hongkai Ji
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