Welcome to the SCRATCH download page.
Thank you for your interest.
All software and related material contained herein can be downloaded freely for academic, non-commercial, research use on ly.
For any other use, please contact pfbaldi@ics.uci.edu.
Copyright 2006. Institute for Genomics and Bioinformatics. University of California, Irvine. USA.
1. SSpro/ACCpro 4.03: Protein Secondary Structure (3-class) and Solvent Accessibility(20-class) Prediction
Download SSpro and ACCpro 4.03 package (Linux version (1.6GB),
Solaris version (3.1GB) ) |
Access SSpro 4.0 Web Server |
Installation instructions.
SSpro/ACCpro 4 is the first hybrid approach of combining neural network (ab initio) and homology analysis to improve the prediction of secondary structure and solvent accessibility.
Reference:
J. Cheng, A. Randall, M. Sweredoski, P. Baldi, SCRATCH: a Protein Structure and
Structural Feature Prediction Server, Nucleic Acids Research,
vol. 33 (web server issue), w72-76, 2005.[PDF] [PDF at NAR website]
2. MUpro 1.1: Prediction of Stability Changes (delta delta G) of Single Site Mutations from Protein Sequences
Download MUpro 1.1 source code and executable (200K, Linux version) | Installation instructions | Access MUpro server | MUpro dataset (1615 mutations) | MUpro dataset (388 mutations)
Reference:
J. Cheng A. Randall, P. Baldi. Prediction of Protein Stability Changes for Single-Site Mutations Using Support Vector Machines. Proteins, vol. 62, no. 4, pp. 1125-1132, 2006.
[PDF][PDF at Proteins website]
3. DOMpro 1.0: Protein Domain Prediction
Download DOMpro 1.0 (Linux version, about 1M)
| Access DOMpro web server | Multi-domain dataset | Single domain dataset
Reference:
J. Cheng, M. Sweredoski, P. Baldi. DOMpro: Protein Domain Prediction Using Profiles, Secondary Structure, Relative Solvent Accessibility, and Recursive Neural Networks. Knowledge Discovery and Data Mining, vol. 13, no. 1, pp. 1-20, 2006. [PDF]
4. DIpro 2.0: Protein Disulfide Bond Prediction
Download DIpro 2.0 here (Linux version) |
Access DIpro Web Server
|Download Dataset
Reference:
[1] J. Cheng, H. Saigo, P. Baldi, Large-Scale Prediction of Disulphide Bridges Using Kernel Methods, Two-Dimensional Recursive Neural Networks, and Weighted Graph Matching, Proteins, vol. 62, no. 3, pp. 617-629, 2006. [PDF] [PDF at Proteins website]
[2] P. Baldi, J. Cheng, A. Vullo, Large-Scale Prediction of Disulphide Bond Connectivity , Advances in Neural Information Processing Systems 17 (NIPS 2004), L. Saul,Y. Weiss, and L. Bottou editors, MIT press, pp.97-104, Cambridge, MA, 2005. [PDF]
[PDF at NIPS website]