Methodology article
A simplified approach to disulfide connectivity prediction from protein sequences
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* Corresponding author: Paolo Frasconi p-f@dsi.unifi.it
Machine Learning and Neural Networks Group, Dipartimento di Sistemi e Informatica, Università degli Studi di Firenze, Via di Santa Marta 3, 50139 Firenze, Italy
BMC Bioinformatics 2008, 9:20 doi:10.1186/1471-2105-9-20
Published: 14 January 2008Additional files
Additional file 1:
PDBSelect Data set. The archive contains the 1,589 non redundant chains used for the experiments on binary classification of chains and cysteines (see results in Tables 2 and 3).
Format: ZIP Size: 835KB Download file
Additional file 2:
SP39 Data set. The archive contains the 446 chains from SWISS-PROT used for prediction of disulfide connectivity (see results in Table 5).
Format: ZIP Size: 190KB Download file