
Proceedings Paper
Neural network prediction of protein adsorptionFormat | Member Price | Non-Member Price |
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Paper Abstract
The prediction of protein adsorption to surfaces from solution is a perennial unsolved problem in biomedicine, physical
chemistry and other fields. Here we used neural networks and the previously developed Biomolecular Adsorption
Database (BAD) to predict the amount of protein adsorbed by a set of five descriptors of the protein, surface and
solution. We find a moderately good predictive ability if very large adsorption values are present and a good fit if these
few outliers are eliminated. With a growing number of entries in the BAD, we expect the accuracy of the predicted
values to increase substantially. This paper presents for the first time a universal and stand-alone quantitative predictor of
protein adsorption.
Paper Details
Date Published: 2 January 2008
PDF: 6 pages
Proc. SPIE 6799, BioMEMS and Nanotechnology III, 679911 (2 January 2008); doi: 10.1117/12.768952
Published in SPIE Proceedings Vol. 6799:
BioMEMS and Nanotechnology III
Dan V. Nicolau; Derek Abbott; Kourosh Kalantar-Zadeh; Tiziana Di Matteo; Sergey M. Bezrukov, Editor(s)
PDF: 6 pages
Proc. SPIE 6799, BioMEMS and Nanotechnology III, 679911 (2 January 2008); doi: 10.1117/12.768952
Show Author Affiliations
Dan V. Nicolau Jr., Univ. of Oxford (United Kingdom)
Elena Vasina, The Univ. of Liverpool (United Kingdom)
Elena Vasina, The Univ. of Liverpool (United Kingdom)
Ewa Paszek, The Univ. of Liverpool (United Kingdom)
Dan V. Nicolau, The Univ. of Liverpool (United Kingdom)
Dan V. Nicolau, The Univ. of Liverpool (United Kingdom)
Published in SPIE Proceedings Vol. 6799:
BioMEMS and Nanotechnology III
Dan V. Nicolau; Derek Abbott; Kourosh Kalantar-Zadeh; Tiziana Di Matteo; Sergey M. Bezrukov, Editor(s)
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