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Gene regulation in higher eukaryotes involves a complex interplay between the gene proximal promoter and distal genomic elements (such as enhancers) which work in concert to drive spatio-temporal expression. The experimental…

Genomics · Quantitative Biology 2008-03-24 Arvind Rao , Alfred O. Hero , David J. States , James Douglas Engel

Oscillations lie at the core of many biological processes, from the cell cycle, to circadian oscillations and developmental processes. Time-keeping mechanisms are essential to enable organisms to adapt to varying conditions in environmental…

Machine Learning · Statistics 2015-04-27 D Trejo , AJ Millar , G Sanguinetti

In prokaryotic genomes the number of transcriptional regulators is known to quadratically scale with the total number of protein-coding genes. Toolbox model was recently proposed to explain this scaling for metabolic enzymes and their…

Molecular Networks · Quantitative Biology 2010-09-24 Tin Yau Pang , Sergei Maslov

The diversity of expressed genes plays a critical role in cellular specialization, adaptation to environmental changes, and overall cell functionality. This diversity varies dramatically across cell types and is orchestrated by intricate,…

Biological Physics · Physics 2023-11-28 Orr Levy , Shubham Tripathi , Scott D. Pope , Yang Y. Liu , Ruslan Medzhitov

In tumoral cells, gene regulation mechanisms are severely altered, and these modifications in the regulations may be characteristic of different subtypes of cancer. However, these alterations do not necessarily induce differential…

Genetic differences between individuals associated to quantitative phenotypic traits, including disease states, are usually found in non-coding genomic regions. These genetic variants are often also associated to differences in expression…

Molecular Networks · Quantitative Biology 2016-11-02 Lingfei Wang , Tom Michoel

Supervised machine learning is emerging as a powerful computational tool to predict the properties of complex quantum systems at a limited computational cost. In this article, we quantify how accurately deep neural networks can learn the…

Computational Physics · Physics 2020-09-03 N. Saraceni , S. Cantori , S. Pilati

Temporal networks are a class of time-varying networks, which change their topology according to a given time-ordered sequence of static networks (known as subsystems). This paper investigates the reachability and controllability of…

Systems and Control · Electrical Eng. & Systems 2024-05-27 Yuan Zhang , Yuanqing Xia , Long Wang

Gene duplication is a fundamental evolutionary mechanism that contributes to biological complexity and diversity (Fortna et al., 2004). Traditionally, research has focused on the duplication of gene sequences (Zhang, 1914). However,…

Molecular Networks · Quantitative Biology 2024-05-07 Ashley Scruse , Jonathan Arnold , Robert Robinson

Accurately inferring Gene Regulatory Networks (GRNs) is a critical and challenging task in biology. GRNs model the activatory and inhibitory interactions between genes and are inherently causal in nature. To accurately identify GRNs,…

Estimating population-level prevalence and transmission dynamics of wildlife pathogens can be challenging, partly because surveillance data is sparse, detection-driven, and unevenly sequenced. Using highly pathogenic avian influenza A/H5…

Populations and Evolution · Quantitative Biology 2026-01-16 Haley Stone , Jing Du , Yang Yang , Ashna Desai , Rebecca Dawson , Hao Xue , David Heslop , Matthew Scotch , Andreas Züfle , C. Raina MacIntyre , Flora Salim

Systems biology is an emerging interdisciplinary area of research that focuses on study of complex interactions in a biological system, such as gene regulatory networks. The discovery of gene regulatory networks leads to a wide range of…

Neural and Evolutionary Computing · Computer Science 2016-10-13 Khalid Raza , Mansaf Alam

Networks exhibiting "accelerating" growth have total link numbers growing faster than linearly with network size and can exhibit transitions from stationary to nonstationary statistics and from random to scale-free to regular statistics at…

Molecular Networks · Quantitative Biology 2017-12-22 M. J. Gagen , J. S. Mattick

Genetic interaction measures how different genes collectively contribute to a phenotype, and can reveal functional compensation and buffering between pathways under genetic perturbations. Recently, genome-wide screening for genetic…

Molecular Networks · Quantitative Biology 2015-03-17 Gang Fang , Wen Wang , Vanja Paunic , Benjamin Oately , Majda Haznadar , Michael Steinbach , Brian Van Ness , Chad L. Myers , Vipin Kumar

Continuous-time Bayesian Networks (CTBNs) represent a compact yet powerful framework for understanding multivariate time-series data. Given complete data, parameters and structure can be estimated efficiently in closed-form. However, if…

Machine Learning · Statistics 2019-11-04 Dominik Linzner , Michael Schmidt , Heinz Koeppl

Genetic regulatory networks are defined by their topology and by a multitude of continuously adjustable parameters. Here we present a class of simple models within which the relative importance of topology vs. interaction strengths becomes…

Molecular Networks · Quantitative Biology 2013-08-02 Mikhail Tikhonov , William Bialek

Signed networks, i.e., networks with positive and negative edges, commonly arise in various domains from social media to epidemiology. Modeling signed networks has many practical applications, including the creation of synthetic data sets…

Quantitative Methods · Quantitative Biology 2022-11-18 Angelina Brilliantova , Hannah Miller , Ivona Bezáková

Gene regulation in Eukaryotes is mainly effected through transcription factors binding to rather short recognition motifs generally located upstream of the coding region. We present a novel computational method to identify regulatory…

Disordered Systems and Neural Networks · Physics 2007-05-23 M. Caselle , F. Di Cunto , P. Provero

Large datasets represented by multidimensional data point clouds often possess non-trivial distributions with branching trajectories and excluded regions, with the recent single-cell transcriptomic studies of developing embryo being notable…

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