j 2024

Special Issue on Artificial Intelligence for Synthetic Biology

MARTIN, Hector Garcia, Stanislav MAZURENKO and Huimin ZHAO

Basic information

Original name

Special Issue on Artificial Intelligence for Synthetic Biology

Authors

MARTIN, Hector Garcia, Stanislav MAZURENKO and Huimin ZHAO

Edition

ACS Synthetic Biology, American Chemical Society, 2024, 2161-5063

Other information

Language

English

Type of outcome

Článek v odborném periodiku (nerecenzovaný)

Field of Study

10608 Biochemistry and molecular biology

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 4.700 in 2022

Organization unit

Faculty of Science

DOI

UT WoS

001162208500001

Keywords in English

Genetics; Kinetic modeling; Optimization; Peptides and proteins; Synthetic biology

Tags

International impact, Reviewed
Změněno: 24/4/2024 11:00, Mgr. Marie Šípková, DiS.

Abstract

V originále

Synthetic biology presents significant prospects of helping scientists tackle important societal problems. However, a significant hurdle in this endeavor is our inability to predict biological systems as accurately as we predict and simulate physical or chemical ones. This limitation has important fundamental and practical implications: from the practical point of view, we are unable to design biological systems (e.g., proteins, pathways, cells) to a specification (e.g., bind to this molecule with this binding affinity or produce this chemical at this titer, rate, and yield); from the fundamental point of view, we lack an understanding of the underlying mechanisms that produce observed phenotypes. Artificial intelligence (AI) and machine learning (ML) show promise in providing the predictive power that synthetic biology needs and can be applied in all parts of the synthetic biology process (Figure 1).