Browsing by Author "Valencia, Alfonso"
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- myAURA: a personalized health library for epilepsy management via knowledge graph sparsification and visualizationPublication . Correia, Rion Brattig; Rozum, Jordan C.; Cross, Leonard; Felag, Jack; Gallant, Michael; Guo, Ziqi; Herr II, Bruce W.; Min, Aehong; Sanchez-Valle, Jon; Rocha, Deborah Stungis; Valencia, Alfonso; Wang, Xuan; Börner, Katy; Miller, Wendy; Rocha, Luis M.Objectives: Report the development of the patient-centered myAURA application and suite of methods designed to aid epilepsy patients, caregivers, and clinicians in making decisions about self-management and care. Materials and Methods: myAURA rests on an unprecedented collection of epilepsy-relevant heterogeneous data resources, such as biomedical databases, social media, and electronic health records (EHRs). We use a patient-centered biomedical dictionary to link the collected data in a multilayer knowledge graph (KG) computed with a generalizable, open-source methodology. Results: Our approach is based on a novel network sparsification method that uses the metric backbone of weighted graphs to discover important edges for inference, recommendation, and visualization. We demonstrate by studying drug-drug interaction from EHRs, extracting epilepsy-focused digital cohorts from social media, and generating a multilayer KG visualization. We also present our patient-centered design and pilot-testing of myAURA, including its user interface. Discussion: The ability to search and explore myAURA’s heterogeneous data sources in a single, sparsified, multilayer KG is highly useful for a range of epilepsy studies and stakeholder support. Conclusion: Our stakeholder-driven, scalable approach to integrating traditional and nontraditional data sources enables both clinical discovery and data-powered patient self-management in epilepsy and can be generalized to other chronic conditions.
- Sex-specific transcriptome similarity networks elucidate comorbidity relationshipsPublication . Sánchez-Valle, Jon; Flores-Rodero, María; Costa, Felipe Xavier; Carbonell-Caballero, Jose; Núñez-Carpintero, Iker; Tabarés-Seisdedos, Rafael; Rocha, Luis Mateus; Cirillo, Davide; Valencia, AlfonsoHumans present sex-driven biological differences. Consequently, the prevalence of analyzing specific diseases and comorbidities differs between the sexes, directly impacting patients’ management and treatment. Despite its relevance and the growing evidence of said differences across numerous diseases (with 4,370 PubMed results published within the past year), knowledge at the comorbidity level remains limited. In fact, to date, no study has attempted to identify the biological processes altered differently in women and men, promoting differences in comorbidities. To shed light on this problem, we analyze expression data for more than 100 diseases from public repositories, analyzing each sex independently. We calculate similarities between differential expression profiles by disease pairs and find that 13-16% of transcriptomically similar disease pairs are sex-specific. By comparing these results with epidemiological evidence, we recapitulate 53-60% of known comorbidities distinctly described for men and women, finding sex-specific transcriptomic similarities between sex-specific comorbid diseases. The analysis of shared underlying pathways shows that diseases can co-occur in men and women by altering alternative biological processes. Finally, we identify different drugs differentially associated with comorbid diseases depending on patients’ sex, highlighting the need to consider this relevant variable in the administration of drugs due to their possible influence on comorbidities.