Literature DB >> 11471236

CoPreTHi: a Web tool which combines transmembrane protein segment prediction methods.

V J Promponas1, G A Palaios, C M Pasquier, J S Hamodrakas, S J Hamodrakas.   

Abstract

CoPreTHi is a Java based web application, which combines the results of methods that predict the location of transmembrane segments in protein sequences into a joint prediction histogram. Clearly, the joint prediction algorithm, produces superior quality results than individual prediction schemes. The program is available at http://o2.db.uoa.gr/CoPreTHi.

Mesh:

Substances:

Year:  1999        PMID: 11471236

Source DB:  PubMed          Journal:  In Silico Biol        ISSN: 1386-6338


  6 in total

1.  Transmembrane helix predictions revisited.

Authors:  Chien Peter Chen; Andrew Kernytsky; Burkhard Rost
Journal:  Protein Sci       Date:  2002-12       Impact factor: 6.725

2.  Prediction of partial membrane protein topologies using a consensus approach.

Authors:  Johan Nilsson; Bengt Persson; Gunnar Von Heijne
Journal:  Protein Sci       Date:  2002-12       Impact factor: 6.725

3.  Algorithms for incorporating prior topological information in HMMs: application to transmembrane proteins.

Authors:  Pantelis G Bagos; Theodore D Liakopoulos; Stavros J Hamodrakas
Journal:  BMC Bioinformatics       Date:  2006-04-05       Impact factor: 3.169

4.  Evaluation of methods for predicting the topology of beta-barrel outer membrane proteins and a consensus prediction method.

Authors:  Pantelis G Bagos; Theodore D Liakopoulos; Stavros J Hamodrakas
Journal:  BMC Bioinformatics       Date:  2005-01-12       Impact factor: 3.169

Review 5.  A Brief History of Protein Sorting Prediction.

Authors:  Henrik Nielsen; Konstantinos D Tsirigos; Søren Brunak; Gunnar von Heijne
Journal:  Protein J       Date:  2019-06       Impact factor: 2.371

6.  The gene structure and expression of human ABHD1: overlapping polyadenylation signal sequence with Sec12.

Authors:  Alasdair J Edgar
Journal:  BMC Genomics       Date:  2003-05-07       Impact factor: 3.969

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.