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Biomathematical description of synthetic peptide libraries

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Biomathematical description of synthetic peptide libraries. / Sieber, Timo; Hare, Eric; Hofmann, Heike; Trepel, Martin.

In: PLOS ONE, Vol. 10, No. 6, 2015, p. e0129200.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Sieber, T, Hare, E, Hofmann, H & Trepel, M 2015, 'Biomathematical description of synthetic peptide libraries', PLOS ONE, vol. 10, no. 6, pp. e0129200. https://doi.org/10.1371/journal.pone.0129200

APA

Sieber, T., Hare, E., Hofmann, H., & Trepel, M. (2015). Biomathematical description of synthetic peptide libraries. PLOS ONE, 10(6), e0129200. https://doi.org/10.1371/journal.pone.0129200

Vancouver

Sieber T, Hare E, Hofmann H, Trepel M. Biomathematical description of synthetic peptide libraries. PLOS ONE. 2015;10(6):e0129200. https://doi.org/10.1371/journal.pone.0129200

Bibtex

@article{1e39fc767b7b4af09f32fe86beaabc64,
title = "Biomathematical description of synthetic peptide libraries",
abstract = "Libraries of randomised peptides displayed on phages or viral particles are essential tools in a wide spectrum of applications. However, there is only limited understanding of a library's fundamental dynamics and the influences of encoding schemes and sizes on their quality. Numeric properties of libraries, such as the expected number of different peptides and the library's coverage, have long been in use as measures of a library's quality. Here, we present a graphical framework of these measures together with a library's relative efficiency to help to describe libraries in enough detail for researchers to plan new experiments in a more informed manner. In particular, these values allow us to answer-in a probabilistic fashion-the question of whether a specific library does indeed contain one of the {"}best{"} possible peptides. The framework is implemented in a web-interface based on two packages, discreteRV and peptider, to the statistical software environment R. We further provide a user-friendly web-interface called PeLiCa (Peptide Library Calculator, http://www.pelica.org), allowing scientists to plan and analyse their peptide libraries.",
keywords = "Amino Acid Sequence, Molecular Sequence Data, Peptide Library, Peptides, Probability, Software, Journal Article, Research Support, Non-U.S. Gov't",
author = "Timo Sieber and Eric Hare and Heike Hofmann and Martin Trepel",
year = "2015",
doi = "10.1371/journal.pone.0129200",
language = "English",
volume = "10",
pages = "e0129200",
journal = "PLOS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "6",

}

RIS

TY - JOUR

T1 - Biomathematical description of synthetic peptide libraries

AU - Sieber, Timo

AU - Hare, Eric

AU - Hofmann, Heike

AU - Trepel, Martin

PY - 2015

Y1 - 2015

N2 - Libraries of randomised peptides displayed on phages or viral particles are essential tools in a wide spectrum of applications. However, there is only limited understanding of a library's fundamental dynamics and the influences of encoding schemes and sizes on their quality. Numeric properties of libraries, such as the expected number of different peptides and the library's coverage, have long been in use as measures of a library's quality. Here, we present a graphical framework of these measures together with a library's relative efficiency to help to describe libraries in enough detail for researchers to plan new experiments in a more informed manner. In particular, these values allow us to answer-in a probabilistic fashion-the question of whether a specific library does indeed contain one of the "best" possible peptides. The framework is implemented in a web-interface based on two packages, discreteRV and peptider, to the statistical software environment R. We further provide a user-friendly web-interface called PeLiCa (Peptide Library Calculator, http://www.pelica.org), allowing scientists to plan and analyse their peptide libraries.

AB - Libraries of randomised peptides displayed on phages or viral particles are essential tools in a wide spectrum of applications. However, there is only limited understanding of a library's fundamental dynamics and the influences of encoding schemes and sizes on their quality. Numeric properties of libraries, such as the expected number of different peptides and the library's coverage, have long been in use as measures of a library's quality. Here, we present a graphical framework of these measures together with a library's relative efficiency to help to describe libraries in enough detail for researchers to plan new experiments in a more informed manner. In particular, these values allow us to answer-in a probabilistic fashion-the question of whether a specific library does indeed contain one of the "best" possible peptides. The framework is implemented in a web-interface based on two packages, discreteRV and peptider, to the statistical software environment R. We further provide a user-friendly web-interface called PeLiCa (Peptide Library Calculator, http://www.pelica.org), allowing scientists to plan and analyse their peptide libraries.

KW - Amino Acid Sequence

KW - Molecular Sequence Data

KW - Peptide Library

KW - Peptides

KW - Probability

KW - Software

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1371/journal.pone.0129200

DO - 10.1371/journal.pone.0129200

M3 - SCORING: Journal article

C2 - 26042419

VL - 10

SP - e0129200

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 6

ER -