Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
Web Server issue
pubmed:dateCreated
2006-7-17
pubmed:abstractText
NeuroPred is a web application designed to predict cleavage sites at basic amino acid locations in neuropeptide precursor sequences. The user can study one amino acid sequence or multiple sequences simultaneously, selecting from several prediction models and optional, user-defined functions. Logistic regression models are trained on experimentally verified or published cleavage data from mollusks, mammals and insects, and amino acid motifs reported to be associated with cleavage. Confidence interval limits of the probabilities of cleavage indicate the precision of the predictions; these predictions are transformed into cleavage or non-cleavage events according to user-defined thresholds. In addition to the precursor sequence, NeuroPred accepts user-specified cleavage information, providing model accuracy statistics based on observed and predicted cleavages. Neuropred also computes the mass of the predicted peptides, including user-selectable post-translational modifications. The resulting mass list aids the discovery and confirmation of new neuropeptides using mass spectrometry techniques. The NeuroPred application, manual, reference manuscripts and training sequences are available at http://neuroproteomics.scs.uiuc.edu/neuropred.html.
pubmed:grant
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1362-4962
pubmed:author
pubmed:issnType
Electronic
pubmed:day
1
pubmed:volume
34
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
W267-72
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
NeuroPred: a tool to predict cleavage sites in neuropeptide precursors and provide the masses of the resulting peptides.
pubmed:affiliation
Department of Animal Sciences, University of Illinois, Urbana, IL, USA.
pubmed:publicationType
Journal Article, Research Support, N.I.H., Extramural