Literature DB >> 26343819

Managing bioengineering complexity with AI techniques.

Jacob Beal1, Aaron Adler2, Fusun Yaman2.   

Abstract

Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome.
Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Artificial intelligence; Automation; Synthetic biology

Mesh:

Year:  2015        PMID: 26343819     DOI: 10.1016/j.biosystems.2015.08.006

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


  1 in total

Review 1.  Governing Ethical AI Transformation: A Case Study of AuroraAI.

Authors:  Jaana Leikas; Aditya Johri; Marko Latvanen; Nina Wessberg; Antti Hahto
Journal:  Front Artif Intell       Date:  2022-02-10
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.