Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from
Tian Mi1, Jerlin Camilus Merlin, Sandeep Deverasetty
1Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269-2155, USA.
Abstract:
Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.
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