Vacuum and Surface Science
Online ISSN : 2433-5843
Print ISSN : 2433-5835
Special Feature : Research Forefront of Surface and Vacuum Science Developed by Data-Driven Approach
Data-driven Design of Protein- and Cell-resistant Surfaces : A Challenge to Design Biomaterials Using Materials Informatics
Hiroyuki TAHARARudolf Jason KWARIATomohiro HAYASHI
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2019 Volume 62 Issue 3 Pages 141-146

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Abstract

In this review, we present the current situation of designs of biomaterials using techniques of informatics. In particular, we discuss the prediction the responses of proteins and cells toward materials and data-driven design of new biomaterials. We introduce our recent work, in which we analyzed the correlation among chemical structures of molecules constituting self-assembled monolayers (SAMs), amounts of adsorbed protein, a density of adhered platelets by machine learning using an artificial neural network model. The main conclusion is that the quality of the database is a critical factor in determining the accuracy of the prediction and material design. We also discuss technical issues to develop databases efficiently and systematically to expand the possibility of data-driven strategies to design biomaterials.

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この記事はクリエイティブ・コモンズ [表示 - 非営利 4.0 国際]ライセンスの下に提供されています。
https://creativecommons.org/licenses/by-nc/4.0/deed.ja
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