The art of modeling gene regulatory circuits.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Mariana Gómez-Schiavon, Isabel Montejano-Montelongo, F Sophia Orozco-Ruiz, Cristina Sotomayor-Vivas
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引用次数: 0

Abstract

The amazing complexity of gene regulatory circuits, and biological systems in general, makes mathematical modeling an essential tool to frame and develop our understanding of their properties. Here, we present some fundamental considerations to develop and analyze a model of a gene regulatory circuit of interest, either representing a natural, synthetic, or theoretical system. A mathematical model allows us to effectively evaluate the logical implications of our hypotheses. Using our models to systematically perform in silico experiments, we can then propose specific follow-up assessments of the biological system as well as to reformulate the original assumptions, enriching both our knowledge and our understanding of the system. We want to invite the community working on different aspects of gene regulatory circuits to explore the power and benefits of mathematical modeling in their system.

Abstract Image

基因调控回路建模艺术。
基因调控回路乃至整个生物系统都具有惊人的复杂性,因此数学建模是构建和发展我们对其特性理解的重要工具。在此,我们将介绍一些基本的考虑因素,以便开发和分析一个相关基因调控回路的模型,无论是代表自然系统、合成系统还是理论系统。通过数学模型,我们可以有效评估假设的逻辑含义。利用我们的模型系统地进行硅学实验,我们就能对生物系统提出具体的后续评估建议,并重新提出最初的假设,从而丰富我们的知识和对系统的理解。我们希望邀请从事基因调控回路不同方面研究的各界人士共同探索数学建模在其系统中的力量和益处。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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