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We are analyzing https://link.springer.com/article/10.1186/1471-2199-7-3.

Title:
The RIN: an RNA integrity number for assigning integrity values to RNA measurements | BMC Molecular Biology
Description:
Background The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. Methods A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. Results This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Conclusion Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.
Website Age:
28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

rna, features, integrity, model, data, samples, categories, rin, feature, values, information, ratio, figure, degradation, area, number, error, experiments, set, models, table, based, results, electropherogram, size, article, ribosomal, electropherograms, shows, evidence, approach, quality, software, training, target, google, scholar, algorithm, additional, sregion, file, authors, agilent, categorical, peak, full, expression, process, methods, compared,

Topics {✒️}

open access article article download pdf bio-analytical device based 10-fold cross-validation procedure real-time pcr data real-time-pcr experiment voltage-induced size separation automated bio-analytical device real-time pcr experiments iterative forward search laser-induced fluorescence detection privacy choices/manage cookies automated high-throughput approach real-time pcr full size image bio-analytical device rna quality control nucleic acids research thomas ragg authors’ original file rna string material constant background signal artificial neural networks construct feature spaces high gene expression scope andreas schroeder diplomarbeit universität karlsruhe evolutionary parameter optimization full size table rna quality assessment laser-induced fluorescence precise analytical instrumentation parametric kernel estimators collaboration partners ambion acknowledge christine miller electrophoretic traces reveals examining electrophoretic traces assessing rna quality low gene expression rna integrity assessment author information authors experienced expert users rna molecule plays evaluating rna status categories form clusters measuring rna integrity judge rna integrity full access trained neural networks receiver operating characteristics

Schema {🗺️}

WebPage:
      mainEntity:
         headline:The RIN: an RNA integrity number for assigning integrity values to RNA measurements
         description:The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.
         datePublished:2006-01-31T00:00:00Z
         dateModified:2006-01-31T00:00:00Z
         pageStart:1
         pageEnd:14
         license:https://creativecommons.org/licenses/by/2.0
         sameAs:https://doi.org/10.1186/1471-2199-7-3
         keywords:
            Integrity Category
            Model Evidence
            Fast Region
            Ribosomal Band
            Marker Height
            Biochemistry
            general
            Nucleic Acid Chemistry
            Cell Biology
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            issn:
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            volumeNumber:7
            type:
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                        type:PostalAddress
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               affiliation:
                     name:Agilent Technologies
                     address:
                        name:Agilent Technologies, Waldbronn, Germany
                        type:PostalAddress
                     type:Organization
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               affiliation:
                     name:Agilent Technologies
                     address:
                        name:Agilent Technologies, Waldbronn, Germany
                        type:PostalAddress
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                     address:
                        name:Agilent Technologies, Waldbronn, Germany
                        type:PostalAddress
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               affiliation:
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                     address:
                        name:Agilent Technologies, Santa Clara, USA
                        type:PostalAddress
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               type:Person
               name:Wolfram Menzel
               affiliation:
                     name:Universität Karlsruhe, ILKD
                     address:
                        name:Universität Karlsruhe, ILKD, Karlsruhe, Germany
                        type:PostalAddress
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               name:Martin Granzow
               affiliation:
                     name:quantiom bioinformatics GmbH & Co. KG
                     address:
                        name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
                        type:PostalAddress
                     type:Organization
               type:Person
               name:Thomas Ragg
               affiliation:
                     name:quantiom bioinformatics GmbH & Co. KG
                     address:
                        name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
                        type:PostalAddress
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ScholarlyArticle:
      headline:The RIN: an RNA integrity number for assigning integrity values to RNA measurements
      description:The integrity of RNA molecules is of paramount importance for experiments that try to reflect the snapshot of gene expression at the moment of RNA extraction. Until recently, there has been no reliable standard for estimating the integrity of RNA samples and the ratio of 28S:18S ribosomal RNA, the common measure for this purpose, has been shown to be inconsistent. The advent of microcapillary electrophoretic RNA separation provides the basis for an automated high-throughput approach, in order to estimate the integrity of RNA samples in an unambiguous way. A method is introduced that automatically selects features from signal measurements and constructs regression models based on a Bayesian learning technique. Feature spaces of different dimensionality are compared in the Bayesian framework, which allows selecting a final feature combination corresponding to models with high posterior probability. This approach is applied to a large collection of electrophoretic RNA measurements recorded with an Agilent 2100 bioanalyzer to extract an algorithm that describes RNA integrity. The resulting algorithm is a user-independent, automated and reliable procedure for standardization of RNA quality control that allows the calculation of an RNA integrity number (RIN). Our results show the importance of taking characteristics of several regions of the recorded electropherogram into account in order to get a robust and reliable prediction of RNA integrity, especially if compared to traditional methods.
      datePublished:2006-01-31T00:00:00Z
      dateModified:2006-01-31T00:00:00Z
      pageStart:1
      pageEnd:14
      license:https://creativecommons.org/licenses/by/2.0
      sameAs:https://doi.org/10.1186/1471-2199-7-3
      keywords:
         Integrity Category
         Model Evidence
         Fast Region
         Ribosomal Band
         Marker Height
         Biochemistry
         general
         Nucleic Acid Chemistry
         Cell Biology
      image:
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         name:BMC Molecular Biology
         issn:
            1471-2199
         volumeNumber:7
         type:
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            PublicationVolume
      publisher:
         name:BioMed Central
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:Andreas Schroeder
            affiliation:
                  name:Agilent Technologies
                  address:
                     name:Agilent Technologies, Waldbronn, Germany
                     type:PostalAddress
                  type:Organization
                  name:ABP
                  address:
                     name:ABP, Schiphol, The Netherlands
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Odilo Mueller
            affiliation:
                  name:Agilent Technologies
                  address:
                     name:Agilent Technologies, Santa Clara, USA
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
            name:Susanne Stocker
            affiliation:
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                  address:
                     name:Agilent Technologies, Waldbronn, Germany
                     type:PostalAddress
                  type:Organization
                  name:Roche Diagnostics GmbH
                  address:
                     name:Roche Diagnostics GmbH, Penzberg, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Ruediger Salowsky
            affiliation:
                  name:Agilent Technologies
                  address:
                     name:Agilent Technologies, Waldbronn, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Michael Leiber
            affiliation:
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                  address:
                     name:Agilent Technologies, Waldbronn, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Marcus Gassmann
            affiliation:
                  name:Agilent Technologies
                  address:
                     name:Agilent Technologies, Waldbronn, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Samar Lightfoot
            affiliation:
                  name:Agilent Technologies
                  address:
                     name:Agilent Technologies, Santa Clara, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Wolfram Menzel
            affiliation:
                  name:Universität Karlsruhe, ILKD
                  address:
                     name:Universität Karlsruhe, ILKD, Karlsruhe, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Martin Granzow
            affiliation:
                  name:quantiom bioinformatics GmbH & Co. KG
                  address:
                     name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Thomas Ragg
            affiliation:
                  name:quantiom bioinformatics GmbH & Co. KG
                  address:
                     name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
      isAccessibleForFree:1
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      issn:
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      name:BioMed Central
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         type:ImageObject
      name:Agilent Technologies
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      name:Agilent Technologies
      address:
         name:Agilent Technologies, Santa Clara, USA
         type:PostalAddress
      name:Agilent Technologies
      address:
         name:Agilent Technologies, Waldbronn, Germany
         type:PostalAddress
      name:Roche Diagnostics GmbH
      address:
         name:Roche Diagnostics GmbH, Penzberg, Germany
         type:PostalAddress
      name:Agilent Technologies
      address:
         name:Agilent Technologies, Waldbronn, Germany
         type:PostalAddress
      name:Agilent Technologies
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         name:Agilent Technologies, Waldbronn, Germany
         type:PostalAddress
      name:Agilent Technologies
      address:
         name:Agilent Technologies, Waldbronn, Germany
         type:PostalAddress
      name:Agilent Technologies
      address:
         name:Agilent Technologies, Santa Clara, USA
         type:PostalAddress
      name:Universität Karlsruhe, ILKD
      address:
         name:Universität Karlsruhe, ILKD, Karlsruhe, Germany
         type:PostalAddress
      name:quantiom bioinformatics GmbH & Co. KG
      address:
         name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
         type:PostalAddress
      name:quantiom bioinformatics GmbH & Co. KG
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         name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
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Person:
      name:Andreas Schroeder
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Waldbronn, Germany
               type:PostalAddress
            type:Organization
            name:ABP
            address:
               name:ABP, Schiphol, The Netherlands
               type:PostalAddress
            type:Organization
      name:Odilo Mueller
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Santa Clara, USA
               type:PostalAddress
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      email:[email protected]
      name:Susanne Stocker
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Waldbronn, Germany
               type:PostalAddress
            type:Organization
            name:Roche Diagnostics GmbH
            address:
               name:Roche Diagnostics GmbH, Penzberg, Germany
               type:PostalAddress
            type:Organization
      name:Ruediger Salowsky
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Waldbronn, Germany
               type:PostalAddress
            type:Organization
      name:Michael Leiber
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Waldbronn, Germany
               type:PostalAddress
            type:Organization
      name:Marcus Gassmann
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Waldbronn, Germany
               type:PostalAddress
            type:Organization
      name:Samar Lightfoot
      affiliation:
            name:Agilent Technologies
            address:
               name:Agilent Technologies, Santa Clara, USA
               type:PostalAddress
            type:Organization
      name:Wolfram Menzel
      affiliation:
            name:Universität Karlsruhe, ILKD
            address:
               name:Universität Karlsruhe, ILKD, Karlsruhe, Germany
               type:PostalAddress
            type:Organization
      name:Martin Granzow
      affiliation:
            name:quantiom bioinformatics GmbH & Co. KG
            address:
               name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
               type:PostalAddress
            type:Organization
      name:Thomas Ragg
      affiliation:
            name:quantiom bioinformatics GmbH & Co. KG
            address:
               name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Agilent Technologies, Waldbronn, Germany
      name:ABP, Schiphol, The Netherlands
      name:Agilent Technologies, Santa Clara, USA
      name:Agilent Technologies, Waldbronn, Germany
      name:Roche Diagnostics GmbH, Penzberg, Germany
      name:Agilent Technologies, Waldbronn, Germany
      name:Agilent Technologies, Waldbronn, Germany
      name:Agilent Technologies, Waldbronn, Germany
      name:Agilent Technologies, Santa Clara, USA
      name:Universität Karlsruhe, ILKD, Karlsruhe, Germany
      name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany
      name:quantiom bioinformatics GmbH & Co. KG, Weingarten, Germany

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