title: NeuroPID: a classifier of neuropeptide precursors.
abstract: Neuropeptides (NPs) are short secreted peptides produced in neurons. NPs act by activating signaling cascades governing broad functions such as metabolism, sensation and behavior throughout the animal kingdom. NPs are the products of multistep processing of longer proteins, the NP precursors (NPPs). We present NeuroPID (Neuropeptide Precursor Identifier), an online machine-learning tool that identifies metazoan NPPs. NeuroPID was trained on 1418 NPPs annotated as such by UniProtKB. A large number of sequence-based features were extracted for each sequence with the goal of capturing the biophysical and informational-statistical properties that distinguish NPPs from other proteins. Training several machine-learning models, including support vector machines and ensemble decision trees, led to high accuracy (89-94%) and precision (90-93%) in cross-validation tests. For inputs of thousands of unseen sequences, the tool provides a ranked list of high quality predictions based on the results of four machine-learning classifiers. The output reveals many uncharacterized NPPs and secreted cell modulators that are rich in potential cleavage sites. NeuroPID is a discovery and a prediction tool that can be used to identify NPPs from unannotated transcriptomes and mass spectrometry experiments. NeuroPID predicted sequences are attractive targets for investigating behavior, physiology and cell modulation. The NeuroPID web tool is available at http:// neuropid.cs.huji.ac.il.
authors.affiliation: School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel School of Computer Science, Hadassah Academic College, Jerusalem, Israel.
authors.forename: Solange
authors.initials: S
authors.lastname: Karsenty
authors.affiliation: School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
authors.forename: Nadav
authors.initials: N
authors.lastname: Rappoport
authors.affiliation: Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem, Israel.
authors.forename: Dan
authors.initials: D
authors.lastname: Ofer
authors.affiliation: School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
authors.forename: Adva
authors.initials: A
authors.lastname: Zair
authors.affiliation: Department of Biological Chemistry, The Alexander Silberman Institute of Life Sciences, The Sudarsky Center for Computational Biology, The Hebrew University of Jerusalem, Jerusalem, Israel michall@cc.huji.ac.il.
authors.forename: Michal
authors.initials: M
authors.lastname: Linial
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D023281:Genomics; D006801:Humans; D020407:Internet; D009479:Neuropeptides / Q000737:chemistry / Q000145:classification* / Q000235:genetics; D011498:Protein Precursors / Q000737:chemistry / Q000145:classification* / Q000235:genetics; D020539:Sequence Analysis, Protein; D012984:Software
chemical_list: D009479:Neuropeptides; D011498:Protein Precursors