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Titlebook: Evolutionary Systems Biology; Orkun S. Soyer Book 20121st edition The Editor(s) (if applicable) and The Author(s), under exclusive license

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發(fā)表于 2025-3-21 17:48:43 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Evolutionary Systems Biology
編輯Orkun S. Soyer
視頻videohttp://file.papertrans.cn/319/318030/318030.mp4
概述Highlights the diverse array of methodologies and approaches employed in evolutionary systems biology.This book tries to decipher “evolutionary design principles” and the origins of systems level prop
圖書(shū)封面Titlebook: Evolutionary Systems Biology;  Orkun S. Soyer Book 20121st edition The Editor(s) (if applicable) and The Author(s), under exclusive license
描述The book aims to introduce the reader to the emerging field of Evolutionary Systems Biology, which approaches classical systems biology questions within an evolutionary framework. An evolutionary approach might allow understanding the significance of observed diversity, uncover “evolutionary design principles” and extend predictions made in model organisms to others. In addition, evolutionary systems biology can generate new insights into the adaptive landscape by combining molecular systems biology models and evolutionary simulations. This insight can enable the development of more detailed mechanistic evolutionary hypotheses.
出版日期Book 20121st edition
關(guān)鍵詞Systems Biology
版次1
doihttps://doi.org/10.1007/978-1-4614-3567-9
isbn_ebook978-1-4614-3567-9
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Science+Busines
The information of publication is updating

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Evolution In Silico: From Network Structure to Bifurcation Theory,ilico evolution finds both known and original network designs, and can be used to make predictions on biological behaviours. This computation illustrates how complex traits can evolve in an incremental way, and suggests that dynamical systems theory could be used to get new insights towards a predictive evolutionary theory.
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發(fā)表于 2025-3-22 08:06:11 | 只看該作者
Book 20121st editionprinciples” and extend predictions made in model organisms to others. In addition, evolutionary systems biology can generate new insights into the adaptive landscape by combining molecular systems biology models and evolutionary simulations. This insight can enable the development of more detailed mechanistic evolutionary hypotheses.
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發(fā)表于 2025-3-22 10:17:49 | 只看該作者
Book 20121st editionin an evolutionary framework. An evolutionary approach might allow understanding the significance of observed diversity, uncover “evolutionary design principles” and extend predictions made in model organisms to others. In addition, evolutionary systems biology can generate new insights into the ada
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https://doi.org/10.1007/978-1-349-22453-1populations. Here we discuss the quantitative genetics and systems biology approaches for the study of complex trait architecture and discuss why these two disciplines would synergize with each other to answer questions that neither of the two could answer alone.
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