基因表达动力学中的涌现原理

Q3 Computer Science
J. Nacher, T. Ochiai
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引用次数: 1

摘要

全基因组基因表达数据处理的快速发展使我们能够初步了解细胞内组织的一些基本规律和原理,并研究其复杂的调控结构。然而,识别网络中涉及的动态过程的共性并没有遵循相同的发展。特别是,动力学和结构特征之间的耦合在很大程度上仍未发现。在这里,我们回顾了几项研究,这些研究利用微阵列时间序列数据揭示了不同环境条件和疾病状态下基因表达的动态和原理,以及利用信息论揭示了基因表达系统中临界性的出现。此外,我们还描述了通过使用转录动力学信息来探索表征基因网络的问题所做的努力。将转录组织中揭示的涌现原理与动态信息相结合,可能导致基因网络的重构、表征和完整。我们还讨论了几种基于一系列酶催化反应路线和马尔可夫过程的模拟方法,以及将复杂网络性质与随机理论相结合的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Emergent Principles in Gene Expression Dynamics
Rapid advances in data processing of genome-wide gene expression have allowed us to get a first glimpse of some fundamental laws and principles involved in the intra-cellular organization as well as to investigate its complex regulatory architecture. However, the identification of commonalities in dynamical processes involved in networks has not followed the same development. In particular, the coupling between dynamics and structural features remains largely uncovered. Here, we review several works that have addressed the issue of uncovering the gene expression dynamics and principles using micro-array time series data at different environmental conditions and disease states as well as the emer- gence of criticality in gene expression systems by using information theory. Moreover, we also describe the efforts done to explore the question of characterizing gene networks by using transcriptional dynamics information. The combination of the emergent principles uncovered in the transcriptional organization with dynamic information, may lead to recon- struct, characterize and complete gene networks. We also discuss several methods based on simulations of a series of en- zyme-catalyzed reaction routes and Markov processes as well as combination of complex network properties with sto- chastic theory.
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来源期刊
Open Bioinformatics Journal
Open Bioinformatics Journal Computer Science-Computer Science (miscellaneous)
CiteScore
2.40
自引率
0.00%
发文量
4
期刊介绍: The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.
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