Andrej Ridzik, Broňa Brejová. Neuropeptide Recognition by Machine Learning Methods. In V. Kurkova, L. Bajer, V. Svatek, ed., Information Technologies - Applications and Theory (ITAT), number 1003 in CEUR-WS, pp. 72-78, Jasna, Slovakia, 2014.

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Thanks to advances in DNA sequencing and bioinformatics methods,
for many species we know their genomic sequence as well as
sequences of proteins produced by their cells. However, the exact
function of those proteins is often unknown. The goal of our work
is to automatically recognize neuropeptides, special proteins
involved in communication between neurons. Neuropeptides are
created in a cell from longer protein precursors, and our goal is
to determine, if a given protein is a likely precursor and if
yes, which of its parts will serve as neuropeptides. Existing
methods solve only partial aspects of this problem. Our more
comprehensive system uses a combination of support vector
machines and conditional random fields.