Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

Download BibTeX

Title

The parallel genetic algorithm for designing DNA randomizations in a combinatorial protein experiment

Authors

[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2006

Chapter type

paper

Publication language

english

Abstract

EN Evolutionary methods of protein engineering such as phage display have revolutionized drug design and the means of studying molecular binding. In order to obtain the highest experimental efficiency, the distributions of constructed combinatorial libraries should be carefully adjusted. The presented approach takes into account diversity–completeness trade–off and tries to maximize the number of new amino acid sequences generated in each cycle of the experiment. In the paper, the mathematical model is introduced and the parallel genetic algorithm for the defined optimization problem is described. Its implementation on the SunFire 6800 computer proves a high efficiency of the proposed approach.

Pages (from - to)

1097 - 1105

DOI

10.1007/11752578_133

URL

https://link.springer.com/chapter/10.1007/11752578_133

Book

Parallel Processing and Applied Mathematics : 6th International Conference, PPAM 2005, Poznań, Poland, September 11-14, 2005, Revised Selected Papers

Presented on

6th International Conference on Parallel Processing and Applied Mathematics, PPAM 2005, 11-14.09.2005, Poznań, Polska

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.