DISULFIND: a disulfide bonding state and cysteine connectivity prediction server
Alessio Ceroni1, Andrea Passerini, Alessandro Vullo
1Machine Learning and Neural Networks Group, Università degli Studi di Firenze, Dipartimento di Sistemi e Informatica, Via di Santa Marta 3, 50139 Firenze, Italy.
Abstract:
DISULFIND is a server for predicting the disulfide bonding state of cysteines and their disulfide connectivity starting from sequence alone. Optionally, disulfide connectivity can be predicted from sequence and a bonding state assignment given as input. The output is a simple visualization of the assigned bonding state (with confidence degrees) and the most likely connectivity patterns. The server is available at http://disulfind.dsi.unifi.it/.
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