PATRI, a Genomics Data Integration Tool for Biomarker Discovery.
The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and pre...
| Publicado en: | BioMed Research International Vol. 2018; pp. 1 - 14 |
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| Autores principales: | , , , , , , , , , , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/28/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=130381406&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 130381406 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 6/28/2018 vid: 2018 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 130381406 130381406 130381406 10.1155/2018/2012078 130381406 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: PATRI, a Genomics Data Integration Tool for Biomarker Discovery. aug: au: Ukmar, G. Melloni, G. E. M. Raddrizzani, L. Rossi, P. Di Bella, S. Pirchio, M. R. Vescovi, M. Leone, A. Callari, M. Cesarini, M. Somaschini, A. Della Vedova, G. Daidone, M. G. Pettenella, M. Isacchi, A. Bosotti, R. affil: NMS Oncology, Nerviano Medical Sciences Srl, Nerviano, Italy sug: subj: Biological Markers Analysis Genomics Clinical Assessment Tools Graphical User Interface Data Analysis, Statistical Phenotype Validity Sensitivity and Specificity Models, Biological ab: The availability of genomic datasets in association with clinical, phenotypic, and drug sensitivity information represents an invaluable source for potential therapeutic applications, supporting the identification of new drug sensitivity biomarkers and pharmacological targets. Drug discovery and precision oncology can largely benefit from the integration of treatment molecular discriminants obtained from cell line models and clinical tumor samples; however this task demands comprehensive analysis approaches for the discovery of underlying data connections. Here we introduce PATRI (Platform for the Analysis of TRanslational Integrated data), a standalone tool accessible through a user-friendly graphical interface, conceived for the identification of treatment sensitivity biomarkers from user-provided genomics data, associated with information on sample characteristics. PATRI streamlines a translational analysis workflow: first, baseline genomics signatures are statistically identified, differentiating treatment sensitive from resistant preclinical models; then, these signatures are used for the prediction of treatment sensitivity in clinical samples, via random forest categorization of clinical genomics datasets and statistical evaluation of the relative phenotypic features. The same workflow can also be applied across distinct clinical datasets. The ease of use of the PATRI tool is illustrated with validation analysis examples, performed with sensitivity data for drug treatments with known molecular discriminants. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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