The Development and Opportunities of Predictive Biotechnology

被引:3
作者
Nestl, Bettina M. [1 ,2 ]
Nebel, Bernd A. [2 ]
Resch, Verena [2 ]
Schuermann, Martin [1 ,3 ,4 ]
Tischler, Dirk [1 ,5 ]
机构
[1] Joint working Grp biotransformat Assoc Gen & Appl, Theodor Heuss Allee 25, D-60486 Frankfurt, Germany
[2] Innophore GmbH, Am Eisernen Tor 3, A-8010 Graz, Austria
[3] InnoSyn B V, Urmonderbaan 22, NL-6167 RD Geleen, Netherlands
[4] SynSil B V, Urmonderbaan 22, NL-6167 RD Geleen, Netherlands
[5] Ruhr Univ Bochum, Microbial Biotechnol, Univ Str 150, D-44780 Bochum, Germany
关键词
machine learning; big data; artificial intelligence; biocatalysis; bioinformatics; CYCLIC GMP-AMP; PHOSPHOROTHIOATE DNA; STING AGONISTS; LNA; DESIGN; CGAS; OLIGONUCLEOTIDES; 2ND-MESSENGER; INHIBITION; 2'3'-CGAMP;
D O I
10.1002/cbic.202300863
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Recent advances in bioeconomy allow a holistic view of existing and new process chains and enable novel production routines continuously advanced by academia and industry. All this progress benefits from a growing number of prediction tools that have found their way into the field. For example, automated genome annotations, tools for building model structures of proteins, and structural protein prediction methods such as AlphaFold2 (TM) or RoseTTAFold have gained popularity in recent years. Recently, it has become apparent that more and more AI-based tools are being developed and used for biocatalysis and biotechnology. This is an excellent opportunity for academia and industry to accelerate advancements in the field further. Biotechnology, as a rapidly growing interdisciplinary field, stands to benefit greatly from these developments.
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页数:7
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