@article { , title = {Modelling human embryoid body cell adhesion to a combinatorial library of polymer surfaces}, 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.}, doi = {10.1039/C2JM34782B}, eissn = {1364-5501}, issn = {0959-9428}, issue = {22}, journal = {Journal of Materials Chemistry}, publicationstatus = {Published}, publisher = {Royal Society of Chemistry}, url = {https://nottingham-repository.worktribe.com/output/710869}, volume = {39}, year = {2012}, author = {Epa, V.C. and Yang, Jing and Mei, Ying and Hook, Andrew L. and Langer, Robert and Anderson, Daniel G. and Davies, Martyn C. and Alexander, Morgan R. and Winkler, David A.} }