Expertomica metabolite profiling: getting more information from LC-MS using the stochastic systems approach

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12640%2F09%3A00010010" target="_blank" >RIV/60076658:12640/09:00010010 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Expertomica metabolite profiling: getting more information from LC-MS using the stochastic systems approach

Popis výsledku v původním jazyce

Mass spectrometers are sophisticated,. ne instruments which are essential in a variety applications. However, the data they produce are usually interpreted in a rather primitive way, without considering the accuracy of this data and the potential errorsin identifying peaks. Our new approach corrects this situation by dividing the LC-MS output into three components: (i) signature of the analyte, (ii) random noise and (iii) systemic noise. The systemic noise is related to the instrument and to the particular experiment; its characteristics change in time and depend on the analyzed substance. Working with these components allows us to quantify the probability of peak errors and, at the same time, to retrieve some peaks which get lost in the noise when using the existing methods. Our software tool, Expertomica metabolite pro. ling, automatically evaluates the given instrument, detects compounds and calculates the probability of individual peaks. It does not need any artificial user-define

Název v anglickém jazyce

Expertomica metabolite profiling: getting more information from LC-MS using the stochastic systems approach

Popis výsledku anglicky

Mass spectrometers are sophisticated,. ne instruments which are essential in a variety applications. However, the data they produce are usually interpreted in a rather primitive way, without considering the accuracy of this data and the potential errorsin identifying peaks. Our new approach corrects this situation by dividing the LC-MS output into three components: (i) signature of the analyte, (ii) random noise and (iii) systemic noise. The systemic noise is related to the instrument and to the particular experiment; its characteristics change in time and depend on the analyzed substance. Working with these components allows us to quantify the probability of peak errors and, at the same time, to retrieve some peaks which get lost in the noise when using the existing methods. Our software tool, Expertomica metabolite pro. ling, automatically evaluates the given instrument, detects compounds and calculates the probability of individual peaks. It does not need any artificial user-define

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BO - Biofyzika

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název periodika

Bioinformatics

ISSN

1367-4803

e-ISSN

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Svazek periodika

25

Číslo periodika v rámci svazku

20

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

4

Strana od-do

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Kód UT WoS článku

000270685200030

EID výsledku v databázi Scopus

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