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dc.contributor.authorUrda-García, Beatriz
dc.contributor.authorValencia, Alfonso
dc.date.accessioned2021-06-04T07:12:22Z
dc.date.available2021-06-04T07:12:22Z
dc.date.issued2021-05
dc.identifier.citationUrda-García, B.; Valencia, A. From comorbidities to gene expression fingerprints and back. A: . Barcelona Supercomputing Center, 2021, p. 68-69.
dc.identifier.urihttp://hdl.handle.net/2117/346620
dc.description.abstractEpidemiological evidence shows that some diseases tend to co-occur more than expected by chance and that patientspecific trends are observed. However, the molecular processes underlying these phenomena remain unclear. Here we exploit the accumulating RNA-seq data on human diseases to calculate disease similarities at the transcriptomic level. We build a disease similarity network that significantly captures almost half of the medically known comorbidities, substantially outperforming previously published methods and providing biological explanations for such co-occurrences. Additionally, we group patients from a given disease with a similar expression profile into meta-patients and calculate their molecular similarities with the analyzed diseases, highlighting the need to study disease comorbidities within a personalized medicine scope. Finally, we provide a web application in which the networks and their underlying molecular mechanisms can be easily inspected.
dc.format.extent2 p.
dc.languageen
dc.language.isoeng
dc.publisherBarcelona Supercomputing Center
dc.subjectÀrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
dc.subject.lcshHigh performance computing
dc.subject.otherComorbidity
dc.subject.othergene expression
dc.subject.otherRNA-seq
dc.titleFrom comorbidities to gene expression fingerprints and back
dc.typeConference report
dc.subject.lemacCàlcul intensiu (Informàtica)
dc.rights.accessOpen Access
local.citation.startingPage68
local.citation.endingPage69


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