Prediction of beta-barrel membrane proteins by searching for restricted domains

Episode von Medizin - Open Access LMU - Teil 14/22 von Ludwig-Maximilians-Universität München · 1. Januar 2005

Background: The identification of beta-barrel membrane proteins out of a genomic/proteomic background is one of the rapidly developing fields in bioinformatics. Our main goal is the prediction of such proteins in genome/proteome wide analyses. Results: For the prediction of beta-barrel membrane proteins within prokaryotic proteomes a set of parameters was developed. We have focused on a procedure with a low false positive rate beside a procedure with lowest false prediction rate to obtain a high certainty for the predicted sequences. We demonstrate that the discrimination between beta-barrel membrane proteins and other proteins is improved by analyzing a length limited region. The developed set of parameters is applied to the proteome of E. coli and the results are compared to four other described procedures. Conclusion: Analyzing the beta-barrel membrane proteins revealed the presence of a defined membrane inserted beta-barrel region. This information can now be used to refine other prediction programs as well. So far, all tested programs fail to predict outer membrane proteins in the proteome of the prokaryote E. coli with high reliability. However, the reliability of the prediction is improved significantly by a combinatory approach of several programs. The consequences and usability of the developed scores are discussed.

Weitere Episoden von „Medizin - Open Access LMU - Teil 14/22“

Über den Podcast

Die Universitätsbibliothek (UB) verfügt über ein umfangreiches Archiv an elektronischen Medien, das von Volltextsammlungen über Zeitungsarchive, Wörterbücher und Enzyklopädien bis hin zu ausführlichen Bibliographien und mehr als 1000 Datenbanken reicht. Auf iTunes U stellt die UB unter anderem…

Medizin - Open Access LMU - Teil 14/22

Ähnliche Episoden

Alle Episoden von Medizin - Open Access LMU - Teil 14/22 · Mehr Bildung-Podcasts