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2016 | 63 | 3 | 483-491
Article title

Identification of antimicrobial peptides by using eigenvectors

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EN
Abstracts
EN
Antibacterial peptides are subject to broad research due to their potential application and the benefit they can provide for a wide range of diseases. In this work, a mathematical-computational method, called the Polarity Vector Method, is introduced that has a high discriminative level (>70%) to identify peptides associated with Gram (-) bacteria, Gram (+) bacteria, cancer cells, fungi, insects, mammalian cells, parasites, and viruses, taken from the Antimicrobial Peptides Database. This supervised method uses only eigenvectors from the incident polar matrix of the group studied. It was verified with a comparative study with another extensively verified method developed previously by our team, the Polarity Index Method. The number of positive hits of both methods was up to 98% in all the tests conducted.
Year
Volume
63
Issue
3
Pages
483-491
Physical description
Dates
published
2016
received
2015-02-13
revised
2016-02-10
accepted
2016-06-13
(unknown)
2016-06-23
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Document Type
Publication order reference
YADDA identifier
bwmeta1.element.bwnjournal-article-abpv63p483kz
Identifiers
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