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Title:           Personalized cancer therapy prioritization based on driver alteration co-occurrence patterns
Subject:         Genome Medicine, 2020, doi:10.1186/s13073-020-00774-x
Keywords:        Drug-response biomarkers,Driver co-occurrence networks,Precision oncology
Author:          Lidia Mateo
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      Title: Abstract
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     Item: 
      Title: Background
      Destination: sectionSec1
     Item: 
      Title: Methods
      Destination: sectionSec2
      Children: 
       Item: 
        Title: Genomic data processing
        Destination: sectionSec3
       Item: 
        Title: Drug-response data
        Destination: sectionSec4
       Item: 
        Title: Molecular representativity of PDXs
        Destination: sectionSec5
       Item: 
        Title: Drug-response prediction based on Cancer bioMarkers database
        Destination: sectionSec6
       Item: 
        Title: Driver co-occurrence networks
        Destination: sectionSec7
        Children: 
         Item: 
          Title: Differentially altered drivers
          Destination: sectionSec8
         Item: 
          Title: Driver pairs
          Destination: sectionSec9
         Item: 
          Title: Driver co-occurrence networks
          Destination: sectionSec10
       Item: 
        Title: TCT4U drug-response classifiers
        Destination: sectionSec11
       Item: 
        Title: Model interpretation
        Destination: sectionSec12
       Item: 
        Title: Experimental validation in PDXs
        Destination: sectionSec13
       Item: 
        Title: Adaptation of TCT4U to use continuous clinical outcome measurements
        Destination: sectionSec14
     Item: 
      Title: Results
      Destination: sectionSec15
      Children: 
       Item: 
        Title: Driver co-occurrence networks of drug response
        Destination: sectionSec16
       Item: 
        Title: TCT4U: a collection of 53 drug-response classifiers for genome-driven treatment prioritization
        Destination: sectionSec17
       Item: 
        Title: Interpretation of DCO-based predictions
        Destination: sectionSec18
       Item: 
        Title: Experimental validation of TCT4U drug-response predictions on a prospective PDX dataset
        Destination: sectionSec19
       Item: 
        Title: Bringing TCT4U from the workbench to the clinics
        Destination: sectionSec20
     Item: 
      Title: Discussion
      Destination: sectionSec21
     Item: 
      Title: Conclusions
      Destination: sectionSec22
     Item: 
      Title: Supplementary information
      Destination: sectionSec23
     Item: 
      Title: Acknowledgements
      Destination: section1
     Item: 
      Title: Authors’ contributions
      Destination: section2
     Item: 
      Title: Funding
      Destination: section3
     Item: 
      Title: Availability of data and materials
      Destination: section4
     Item: 
      Title: Ethics approval and consent to participate
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     Item: 
      Title: Consent for publication
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     Item: 
      Title: Competing interests
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     Item: 
      Title: Author details
      Destination: section5
     Item: 
      Title: References
      Destination: sectionBib1
     Item: 
      Title: Publisher’s Note
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    Author: Lidia Mateo
    Subject: Genome Medicine, 2020, doi:10.1186/s13073-020-00774-x
    Keywords: Drug-response biomarkers,Driver co-occurrence networks,Precision oncology
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                                    <pdfaField:description>Gives the name of an author.</pdfaField:description>
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                           <pdfaType:description>Specifies the types of editor information: name and ORCID of an editor.</pdfaType:description>
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                                    <pdfaField:name>name</pdfaField:name>
                                    <pdfaField:valueType>Text</pdfaField:valueType>
                                    <pdfaField:description>Gives the name of an editor.</pdfaField:description>
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                                    <pdfaField:valueType>URI</pdfaField:valueType>
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                  <pdfaSchema:schema>PDF/A ID Schema</pdfaSchema:schema>
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