Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces

Epa, V.C.; Yang, Jing; Mei, Ying; Hook, Andrew L.; Langer, Robert; Anderson, Daniel G.; Davies, Martyn C.; Alexander, Morgan R.; Winkler, David A.

Abstract

Designing materials to control biology is an intense focus of biomaterials and regenerative medicine research. Discovering and designing materials with appropriate biological compatibility or active control of cells and tissues is being increasingly undertaken using high
throughput synthesis and assessment methods. We report a relatively simple but powerful machine-learning method of generating modelsthat link microscopic or molecular properties of polymers or other materials to their biological effects. We illustrate the potential of these methods by developing the first robust, predictive, quantitative, and purely computational models of adhesion of human embryonic stem cell embryoid bodies (hEB) to the surfaces of 496-member polymers.

Citation

Epa, V., Yang, J., Mei, Y., Hook, A. L., Langer, R., Anderson, D. G., …Winkler, D. A. (2012). Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces. Journal of Materials Chemistry, 39(22), doi:10.1039/C2JM34782B

• Journal Article Type: Article
• Publication Date: Aug 24, 2012
• Deposit Date: Nov 20, 2015
• Publicly Available Date: Nov 20, 2015
• Journal: Journal of Materials Chemistry
• Print ISSN: 0959-9428
• Electronic ISSN: 1364-5501
• Publisher: Royal Society of Chemistry
• Peer Reviewed: Peer Reviewed
• Volume: 39
• Issue: 22
• DOI: https://doi.org/10.1039/C2JM34782B
• Public URL: http://eprints.nottingham.ac.uk/id/eprint/30872
• Publisher URL: http://pubs.rsc.org/en/Content/ArticleLanding/2012/JM/c2jm34782b#!divAbstract
• Copyright Statement: Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf