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Full-Text Articles in Life Sciences
Minimotif Miner 3.0: Database Expansion And Significantly Improved Reduction Of False-Positive Predictions From Consensus Sequences., Tian Mi, Jerlin Camilus Merlin, Sandeep Deverasetty, Michael R. Gryk, Travis J. Bill, Andrew W. Brooks, Logan Lee, Viraj Rathnayake, Christian A. Ross, David P. Sargeant, Christy L. Strong, Paula Watts, Sanguthevar Rajasekaran, Martin Schiller
Minimotif Miner 3.0: Database Expansion And Significantly Improved Reduction Of False-Positive Predictions From Consensus Sequences., Tian Mi, Jerlin Camilus Merlin, Sandeep Deverasetty, Michael R. Gryk, Travis J. Bill, Andrew W. Brooks, Logan Lee, Viraj Rathnayake, Christian A. Ross, David P. Sargeant, Christy L. Strong, Paula Watts, Sanguthevar Rajasekaran, Martin Schiller
Life Sciences Faculty Research
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 …