alexa The Paragon Algorithm, a next generation search engine that uses sequence temperature values and feature probabilities to identify peptides from tandem mass spectra.
Pharmaceutical Sciences

Pharmaceutical Sciences

Journal of Clinical & Experimental Pharmacology

Author(s): Shilov IV, Seymour SL, Patel AA, Loboda A, Tang WH,

Abstract Share this page

Abstract The Paragon Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user interface that removes the user expertise requirement, presenting control settings in the language of the laboratory that are translated to optimal algorithmic settings. To validate this new algorithm, a comparison with Mascot is presented for a series of analogous searches to explore the relative impact of increasing search space probed with Mascot by relaxing the tryptic digestion conformance requirements from trypsin to semitrypsin to no enzyme and with the Paragon Algorithm using its Rapid mode and Thorough mode with and without tryptic specificity. Although they performed similarly for small search space, dramatic differences were observed in large search space. With the Paragon Algorithm, hundreds of biological and artifact modifications, all possible substitutions, and all levels of conformance to the expected digestion pattern can be searched in a single search step, yet the typical cost in search time is only 2-5 times that of conventional small search space. Despite this large increase in effective search space, there is no drastic loss of discrimination that typically accompanies the exploration of large search space. This article was published in Mol Cell Proteomics and referenced in Journal of Clinical & Experimental Pharmacology

Relevant Expert PPTs

Relevant Speaker PPTs

Recommended Conferences

Relevant Topics

Peer Reviewed Journals
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2017-18
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri, Food, Aqua and Veterinary Science Journals

Dr. Krish

1-702-714-7001 Extn: 9040

Clinical and Biochemistry Journals

Datta A

1-702-714-7001Extn: 9037

Business & Management Journals


1-702-714-7001Extn: 9042

Chemical Engineering and Chemistry Journals

Gabriel Shaw

1-702-714-7001 Extn: 9040

Earth & Environmental Sciences

Katie Wilson

1-702-714-7001Extn: 9042

Engineering Journals

James Franklin

1-702-714-7001Extn: 9042

General Science and Health care Journals

Andrea Jason

1-702-714-7001Extn: 9043

Genetics and Molecular Biology Journals

Anna Melissa

1-702-714-7001 Extn: 9006

Immunology & Microbiology Journals

David Gorantl

1-702-714-7001Extn: 9014

Informatics Journals

Stephanie Skinner

1-702-714-7001Extn: 9039

Material Sciences Journals

Rachle Green

1-702-714-7001Extn: 9039

Mathematics and Physics Journals

Jim Willison

1-702-714-7001 Extn: 9042

Medical Journals

Nimmi Anna

1-702-714-7001 Extn: 9038

Neuroscience & Psychology Journals

Nathan T

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

John Behannon

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

1-702-714-7001 Extn: 9042

© 2008-2017 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version