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Network inference approaches are now widely used in biological applications to probe regulatory relationships between molecular components such as genes or proteins. Many methods have been proposed for this setting, but the connections and…

Applications · Statistics 2014-06-03 Chris. J. Oates , Sach Mukherjee

Interactions between genes and gene products give rise to complex circuits that enable cells to process information and respond to external signals. Theoretical studies often describe these interactions using continuous, stochastic, or…

Molecular Networks · Quantitative Biology 2007-05-23 Madalena Chaves , Reka Albert , Eduardo D. Sontag

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

A blood cell lineage consists of several consecutive developmental stages from the pluri- or multipotent stem cell to a state of terminal differentiation. Despite their importance for human biology, the regulatory pathways and gene networks…

Molecular Networks · Quantitative Biology 2020-09-18 Maryam Nazarieh , Volkhard Helms , Marc P. Hoeppner , Andre Franke

Gene regulatory networks (GRNs) are essential for understanding cell fate decisions and disease mechanisms, yet cross-species GRN inference from single-cell RNA-seq data remains challenging due to noise, sparsity, and cross-species…

Genomics · Quantitative Biology 2026-01-19 Shuai Yan , Qingzhi Yu , Wengfeng Dai , Xiang Cheng

Characterization of the differences between biological and random networks can reveal the design principles that enable the robust realization of crucial biological functions including the establishment of different cell types. Previous…

Molecular Networks · Quantitative Biology 2020-08-26 Shubham Tripathi , David A. Kessler , Herbert Levine

The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which…

Biological Physics · Physics 2012-02-17 J. Sanz , E. Cozzo , J. Borge-Holthoefer , Y. Moreno

Module network inference is a statistical method to reconstruct gene regulatory networks, which uses probabilistic graphical models to learn modules of coregulated genes and their upstream regulatory programs from genome-wide gene…

Quantitative Methods · Quantitative Biology 2019-05-28 Pau Erola , Eric Bonnet , Tom Michoel

A system level view of cellular processes for human and several organisms can be cap- tured by analyzing molecular interaction networks. A molecular interaction network formed of differentially expressed genes and their interactions helps…

Molecular Networks · Quantitative Biology 2016-11-09 Jeethu V. Devasia , Priya Chandran

Two different types of directed networks are investigated, transcriptional regulation networks and neural networks. The directed network structure are studied and also shown to reflect the different processes taking place on the networks.…

Disordered Systems and Neural Networks · Physics 2016-08-16 Andreas Grönlund

Understanding how gene regulatory networks (GRNs) give rise to stable and dynamic cellular states remains a central challenge in theoretical biology, particularly when slow epigenetic feedback reshapes the underlying regulatory landscape.…

Molecular Networks · Quantitative Biology 2026-04-15 Sascha H. Hauck , Sandip Saha , Narsis A. Kiani , Jesper N. Tegner

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in animals and plants. Genes regulated by miRNAs…

Applications · Statistics 2011-01-10 Francesco C. Stingo , Yian A. Chen , Marina Vannucci , Marianne Barrier , Philip E. Mirkes

Background: Gene regulatory networks coordinate the expression of genes across physiological states and ensure a synchronized expression of genes in cellular subsystems, critical for the coherent functioning of cells. Here we address the…

Molecular Networks · Quantitative Biology 2021-07-28 Ian Leifer , Mishael Sánchez-Pérez , Cecilia Ishida , Hernán A. Makse

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node…

Molecular Networks · Quantitative Biology 2016-07-11 Fernando Antoneli , Renata C. Ferreira , Marcelo R. S. Briones

Cellular signaling is essential in information processing and decision making. Therefore, a variety of experimental approaches have been developed to study signaling on bulk and single-cell level. Single-cell measurements of signaling…

Quantitative Methods · Quantitative Biology 2019-04-18 Carolin Loos , Jan Hasenauer

Diseases involve complex processes and modifications to the cellular machinery. The gene expression profile of the affected cells contains characteristic patterns linked to a disease. Hence, biological knowledge pertaining to a disease can…

Quantitative Methods · Quantitative Biology 2020-04-13 Thomas Gaudelet , Noel Malod-Dognin , Jon Sanchez-Valle , Vera Pancaldi , Alfonso Valencia , Natasa Przulj

Coregulation of the expression of groups of genes has been extensively demonstrated empirically in bacterial and eukaryotic systems. Such coregulation can arise through the use of shared regulatory motifs, which allow the coordinated…

Machine Learning · Statistics 2016-04-12 Jonathan H. Warrell , Musa M. Mhlanga

Molecular networks guide the biochemistry of a living cell on multiple levels: its metabolic and signalling pathways are shaped by the network of interacting proteins, whose production, in turn, is controlled by the genetic regulatory…

Soft Condensed Matter · Physics 2009-11-07 Sergei Maslov , Kim Sneppen

MicroRNAs (miRNAs) are endogenous 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3-noncoding region of specific message RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs…

Molecular Networks · Quantitative Biology 2007-05-23 Qinghua Cui , Zhenbao Yu , Enrico O. Purisima , Edwin Wang

The computational modeling of genetic regulatory networks is now common place, either by fitting a system to experimental data or by exploring the behaviour of abstract systems with the aim of identifying underlying principles. This paper…

Computational Engineering, Finance, and Science · Computer Science 2013-10-22 Larry Bull
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