From owner-announce@net.bio.net Wed Sep 29 16:43:00 1999 Path: biosci!biosci!not-for-mail From: James Cuff Newsgroups: bionet.announce Subject: ANNOUNCE: Jnet secondary structure prediction method Date: 29 Sep 1999 10:43:49 -0700 Organization: MRC Human Genome Mapping Project Resource Centre Lines: 47 Sender: daemon@net.bio.net Approved: kristoff@net.bio.net Distribution: world Message-ID: <7stj4l$9nm@net.bio.net> NNTP-Posting-Host: net.bio.net /* Announcing Jnet v0.1 (alpha) */ Jnet is a new consensus neural network protein secondary structure prediction method. The software is freely available to all. The method works through the application of multiple sequence alignments, alongside PSIBLAST and HMM profiles. Consensus techniques are applied to predict the final secondary structure more accurately than the component predictions. - Average Q3 prediction accuracy is 76.4% (8.4sd). This figure is based on a set of 406 non-redundant proteins that were not applied during the development of the method. - Residues predicted with a confidence value of 5 or greater have an average Q3 accuracy of 84%, and cover more than 68% of residues. - Relative solvent accessibility based on a two state model, for 25, 5 and 0% accessibility is predicted at 76.2, 79.8 and 86.6% respectively. - Availability: The Jnet homepage can be accessed at: http://circinus.ebi.ac.uk:8081/jnet and from the software pages of the Barton group web server at the EBI: http://barton.ebi.ac.uk/ SGI and Linux binaries are available, along with the C source code. Full details of the method are described in: "Application of enhanced multiple sequence alignment profiles to improve protein secondary structure prediction", Cuff, J. A., Barton, G. J., (submitted) 1999. James Cuff, Geoff. Barton European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge. CB10 1SD .