Detailed Information on Publication Record
2007
Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics
HAVLIŠ, Jan and Lenka MONINCOVÁBasic information
Original name
Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics
Name in Czech
Předpověď retenčních časů tryptických peptidů pomocí tzv. měkkého modelování jako nástroj pro proteomiku vedenou kapalinovou chromatografií a hmotnostní spektrometrií
Authors
HAVLIŠ, Jan (203 Czech Republic, guarantor, belonging to the institution) and Lenka MONINCOVÁ (203 Czech Republic, belonging to the institution)
Edition
Trends in Chromatography, Indie, Research Trends (P) Ltd. 2007, 0972-8635
Other information
Language
English
Type of outcome
Článek v odborném periodiku
Field of Study
10406 Analytical chemistry
Country of publisher
India
Confidentiality degree
není předmětem státního či obchodního tajemství
RIV identification code
RIV/00216224:14310/07:00026284
Organization unit
Faculty of Science
Keywords in English
retention time;prediction;proteomics;tryptic peptides;liquid chromatography;mass spectrometry
Tags
Tags
International impact, Reviewed
Změněno: 3/10/2011 10:40, doc. Mgr. Jan Havliš, Dr.
V originále
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 spectrometric data 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 choice of 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 retention time, more justified identifications can be made out of collected data. The review deals with summarisation of contemporary knowledge of soft model based prediction of peptide retention time with a special attention given to artificial neural networks.
In Czech
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 článek shrnuje současný stav poznatků na tomto poli se zvláštním zřetelem k využití umělých neuronových sítí.
Links
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| MSM0021622415, plan (intention) |
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