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Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F07%3A00026284" target="_blank" >RIV/00216224:14310/07:00026284 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics

  • Original language description

    To predict a retention time of analyte is already thoroughly researched topic. The knowledge of retention time value could serve many purposes, in LC-MS driven proteomics to know retention time of peptide may help to deal with acquired mass spectrometricdata in order to maximise the information gain by means of number of identified peptides. Among the two principal approaches how to determine the retention time of compound, hard and soft modelling, the soft models have the advantage of being based on black box principle, what means the relations between respective retention time and compound properties in combination with separation system properties can be found without any exact knowledge of physico-chemical relation between them. The proper choiceof compound descriptors and relevant settings of separation system may result in precise determination of retention time. As for the proteomics application, once it is possible to make a link between tryptic peptide sequence and its reten

  • Czech name

    Předpověď retenčních časů tryptických peptidů pomocí tzv. měkkého modelování jako nástroj pro proteomiku vedenou kapalinovou chromatografií a hmotnostní spektrometrií

  • Czech description

    Předpověď retenčních časů tryptických peptidů může významně sloužit v proteomice podporované LC-MS ke zkvalitnění identifikace proteinů pomocí de novo sekvenování využitím informace o retenčním čase, jež je též závislý na sekvenci. Tento přehledný článekshrnuje současný stav poznatků na tomto poli se zvláštním zřetelem k využití umělých neuronových sítí.

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    CB - Analytical chemistry, separation

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2007

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Trends in Chromatography

  • ISSN

    0972-8635

  • e-ISSN

  • Volume of the periodical

    3

  • Issue of the periodical within the volume

    -

  • Country of publishing house

    IN - INDIA

  • Number of pages

    8

  • Pages from-to

  • UT code for WoS article

  • EID of the result in the Scopus database