Cargando…

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Mi, Tian, Merlin, Jerlin Camilus, Deverasetty, Sandeep, Gryk, Michael R., Bill, Travis J., Brooks, Andrew W., Lee, Logan Y., Rathnayake, Viraj, Ross, Christian A., Sargeant, David P., Strong, Christy L., Watts, Paula, Rajasekaran, Sanguthevar, Schiller, Martin R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3245078/
https://www.ncbi.nlm.nih.gov/pubmed/22146221
http://dx.doi.org/10.1093/nar/gkr1189
Descripción
Sumario: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.