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rdf:type
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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 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.
- 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. (en)
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Title
| - Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics
- Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics (en)
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skos:prefLabel
| - Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics
- Prediction of tryptic peptide retention times by means of soft modelling as a tool for liquid chromatography-mass spectrometry driven proteomics (en)
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skos:notation
| - RIV/00216224:14310/07:00026284!RIV10-MSM-14310___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
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http://linked.open...iv/cisloPeriodika
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http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
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http://linked.open...ai/riv/idVysledku
| - RIV/00216224:14310/07:00026284
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http://linked.open...riv/jazykVysledku
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http://linked.open.../riv/klicovaSlova
| - retention time; prediction; proteomics; tryptic peptides; liquid chromatography; mass spectrometry (en)
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http://linked.open.../riv/klicoveSlovo
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http://linked.open...odStatuVydavatele
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http://linked.open...ontrolniKodProRIV
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http://linked.open...i/riv/nazevZdroje
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http://linked.open...in/vavai/riv/obor
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http://linked.open...ichTvurcuVysledku
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http://linked.open...cetTvurcuVysledku
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http://linked.open...UplatneniVysledku
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http://linked.open...v/svazekPeriodika
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http://linked.open...iv/tvurceVysledku
| - Monincová, Lenka
- Havliš, Jan
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http://linked.open...n/vavai/riv/zamer
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issn
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number of pages
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http://localhost/t...ganizacniJednotka
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