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Transcriptomic data is a treasure-trove in modern molecular biology, as it offers a comprehensive viewpoint into the intricate nuances of gene expression dynamics underlying biological systems. This genetic information must be utilised to…

分子网络 · 定量生物学 2023-12-13 Vikram Singh , Vikram Singh

Cellular phenotypes are determined by the dynamical activity of networks of co-regulated genes. Elucidating such networks is crucial for the understanding of normal cell physiology as well as for the dissection of complex pathologic…

分子网络 · 定量生物学 2007-05-23 Kai Wang , Nilanjana Banerjee , Adam Margolin , Ilya Nemenman , Katia Basso , Riccardo Favera , Andrea Califano

Genetic regulatory networks enable cells to respond to the changes in internal and external conditions by dynamically coordinating their gene expression profiles. Our ability to make quantitative measurements in these biochemical circuits…

生物物理 · 物理学 2015-03-17 Aleksandra M Walczak , Gašper Tkačik

Modelling gene regulatory networks not only requires a thorough understanding of the biological system depicted but also the ability to accurately represent this system from a mathematical perspective. Throughout this chapter, we aim to…

定量方法 · 定量生物学 2018-05-04 Olivia Angelin-Bonnet , Patrick J. Biggs , Matthieu Vignes

Biological systems and processes are networks of complex nonlinear regulatory interactions between nucleic acids, proteins, and metabolites. A natural way in which to represent these interaction networks is through the use of a graph. In…

分子网络 · 定量生物学 2023-01-04 Jacob Rast

Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding…

计算工程、金融与科学 · 计算机科学 2012-05-10 Khalid Raza , Rafat Parveen

Gene Regulatory Networks are networks of interactions in biological organisms responsible for determining the production levels of proteins and peptides. Proteins are workers of a cell factory, and their production defines the goal of a…

神经与进化计算 · 计算机科学 2022-09-12 Iliya Miralavy , Wolfgang Banzhaf

Identity, response to external stimuli, and spatial architecture of a living system are central topics of molecular biology. Presently, they are largely seen as a result of the interplay between a gene repertoire and the regulatory…

分子网络 · 定量生物学 2007-05-23 M. Cosentino Lagomarsino , P. Jona , B. Bassetti

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…

应用统计 · 统计学 2014-06-03 Chris. J. Oates , Sach Mukherjee

Biological networks provide insight into the complex organization of biological processes in a cell at the system level. They are an effective tool for understanding the comprehensive map of functional interactions, finding the functional…

分子网络 · 定量生物学 2017-09-14 Somaye Hashemifar

Gene Regulatory Network (GRN) plays an important role in knowing insight of cellular life cycle. It gives information about at which different environmental conditions genes of particular interest get over expressed or under expressed.…

计算工程、金融与科学 · 计算机科学 2013-10-10 Chanda Panse , Dr. Manali Kshirsagar

Transcriptional regulatory network inference methods have been studied for years. Most of them relie on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this…

基因组学 · 定量生物学 2012-08-03 Jianlong Qi , Tom Michoel

Gene/protein interactions provide critical information for a thorough understanding of cellular processes. Recently, considerable interest and effort has been focused on the construction and analysis of genome-wide gene networks. The large…

分子网络 · 定量生物学 2022-04-25 Xin Li , Hsinchun Chen , Zan Huang , Hua Su , Jesse D. Martinez

Increasing evidence has shown that gene-gene interactions have important effects on biological processes of human diseases. Due to the high dimensionality of genetic measurements, existing interaction analysis methods usually suffer from a…

统计方法学 · 统计学 2021-01-11 Xing Qin , Shuangge Ma , Mengyun Wu

Stochastic reaction network models are widely utilized in biology and chemistry to describe the probabilistic dynamics of biochemical systems in general, and gene interaction networks in particular. Most often, statistical analysis and…

定量方法 · 定量生物学 2017-10-18 Eugenio Cinquemani

Regulatory interactions between genes show a large amount of cross-species variability, even when the underlying functions are conserved: There are many ways to achieve the same function. Here we investigate the ability of regulatory…

分子网络 · 定量生物学 2015-05-13 Franck Stauffer , Johannes Berg

Biological systems are driven by intricate interactions among the complex array of molecules that comprise the cell. Many methods have been developed to reconstruct network models of those interactions. These methods often draw on large…

分子网络 · 定量生物学 2018-06-29 Marieke Lydia Kuijjer , Matthew Tung , GuoCheng Yuan , John Quackenbush , Kimberly Glass

Inference of gene regulatory networks has been an active area of research for around 20 years, leading to the development of sophisticated inference algorithms based on a variety of assumptions and approaches. With the always increasing…

分子网络 · 定量生物学 2022-11-03 Malvina Marku , Vera Pancaldi

The human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown of the entire network. Identifying and…

数据分析、统计与概率 · 物理学 2012-03-02 Amir Bashan , Ronny P. Bartsch , Jan W. Kantelhardt , Shlomo Havlin , Plamen Ch. Ivanov

Motivation: Gene regulatory interactions are of fundamental importance to various biological functions and processes. However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes…

分子网络 · 定量生物学 2017-02-09 Shupeng Gui , Rui Chen , Liang Wu , Ji Liu , Hongyu Miao
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