Keck Graduate Institute of Applied Life Sciences

Developed for SPAM (Systematic Protein Annotation & Modeling) project

The SPAM project is based on work sponsored by the National Institues of Heath (NIH) and its National Institute of General Medical Sciences (NIGMS) division under Grant Number 1 P01 GM63208 (NIH/NIGMS grant title: Tools & Data Resources in Support of Structural Genomics). This five-year grant supports the collaborative efforts of the San Diego Supercomputer Center (SDSC) at the University of California San Diego, the Keck Graduate Institute (KGI), and the Burnham Institute to develop a community resource for systematic protein annotation and modeling (SPAM).

Bayesian Network Model for Protein Fold Recognition

Reference: Raval, A., Ghahramani, Z., and Wild, D.L. (2002) A Bayesian network model for protein fold and remote homologue recognition. Bioinformatics, 18(6):788-801[Abstract][PDF]

SCOP descriptions of the 89 superfamilies modelled can be found here.

Submit a single amino acid sequence for protein fold prediction:

Please enter your e-mail address:

Please enter your sequence in FASTA format(first line starting with > and the title reference, followed by multiple lines of amino acid sequence):

Please send questions and comments to david_wild@kgi.edu

This page is maintained by Seungwoo Hwang