将肢体再生中的功能数据与解剖结果联系起来的生物信息学专家系统。

Daniel Lobo, Erica B Feldman, Michelle Shah, Taylor J Malone, Michael Levin
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引用次数: 0

摘要

两栖动物和蜕皮节肢动物具有非凡的断肢再生能力,这在大量的实验性切割、截肢、移植和分子技术文献中都有描述。尽管有丰富的实验历史,但还没有一个全面的机理模型可以解释这些实验中观察到的模式调节。虽然生物信息学算法已经彻底改变了信号通路的研究,但迄今为止还没有此类工具可以帮助科学家建立与肢体再生领域已发表数据相匹配的大规模形态发生的可检验模型。阻碍算法方法的主要障碍是缺乏对实验再生信息的正式描述,以及缺乏集中存储和挖掘肢体再生功能数据的资源库。建立新的形状生物信息学将大大加快发现复杂再生机制的关键见解。在这里,我们描述了一种新颖的肢体再生数学本体论,以明确编码表型、操作和实验数据。在这一形式主义的基础上,我们提出了第一个集中式正式数据库,其中包含已发表的肢体再生实验以及一个用户友好的专家系统工具,以方便访问和挖掘。这些资源可供社区免费使用,将有助于人类生物学家和人工智能系统发现可检验的肢体再生机理模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration.

A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration.

A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration.

A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration.

Amphibians and molting arthropods have the remarkable capacity to regenerate amputated limbs, as described by an extensive literature of experimental cuts, amputations, grafts, and molecular techniques. Despite a rich history of experimental efforts, no comprehensive mechanistic model exists that can account for the pattern regulation observed in these experiments. While bioinformatics algorithms have revolutionized the study of signaling pathways, no such tools have heretofore been available to assist scientists in formulating testable models of large-scale morphogenesis that match published data in the limb regeneration field. Major barriers preventing an algorithmic approach are the lack of formal descriptions for experimental regenerative information and a repository to centralize storage and mining of functional data on limb regeneration. Establishing a new bioinformatics of shape would significantly accelerate the discovery of key insights into the mechanisms that implement complex regeneration. Here, we describe a novel mathematical ontology for limb regeneration to unambiguously encode phenotype, manipulation, and experiment data. Based on this formalism, we present the first centralized formal database of published limb regeneration experiments together with a user-friendly expert system tool to facilitate its access and mining. These resources are freely available for the community and will assist both human biologists and artificial intelligence systems to discover testable, mechanistic models of limb regeneration.

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