Improving protein solubility and activity by introducing small peptide tags designed with machine learning models-Reference-Cited by-同舟云学术

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Improving protein solubility and activity by introducing small peptide tags designed with machine learning models

Published:2020-12 Issue: Volume:11 Page:e00138
ISSN:2214-0301
Container-title:Metabolic Engineering Communications
language:en
Short-container-title:Metabolic Engineering Communications

Author:

Han Xi,Ning Wenbo,Ma Xiaoqiang,Wang Xiaonan,Zhou Kang

Funder

Singapore Ministry of Education

Singapore MOE

Singapore National Research Foundation

Disruptive & Sustainable Technologies for Agricultural Precision

Publisher

Elsevier BV

Subject

Biomedical Engineering,Endocrinology, Diabetes and Metabolism

Reference38 articles.

1. Sequence-based prediction of protein solubility;Agostini;J. Mol. Biol.,2012

2. High level expression and rational mutagenesis of a designed protein, the minibody: from an insoluble to a soluble molecule;Bianchi;J. Mol. Biol.,1994

3. End to End Learning for Self-Driving Cars;Bojarski,2016

4. Soluble expression of proteins correlates with a lack of positively-charged surface;Chan;Sci. Rep.,2013

5. Learning to predict expression efficacy of vectors in recombinant protein production;Chan;BMC Bioinf.,2010

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