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Publications

Journal Articles


  • STRIDE--An integrated standards-based translational research informatics platform. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium Lowe, H. J., Ferris, T. A., Hernandez, P. M., Weber, S. C. 2009; 2009: 391-395

    Abstract

    STRIDE (Stanford Translational Research Integrated Database Environment) is a research and development project at Stanford University to create a standards-based informatics platform supporting clinical and translational research. STRIDE consists of three integrated components: a clinical data warehouse, based on the HL7 Reference Information Model (RIM), containing clinical information on over 1.3 million pediatric and adult patients cared for at Stanford University Medical Center since 1995; an application development framework for building research data management applications on the STRIDE platform and a biospecimen data management system. STRIDE's semantic model uses standardized terminologies, such as SNOMED, RxNorm, ICD and CPT, to represent important biomedical concepts and their relationships. The system is in daily use at Stanford and is an important component of Stanford University's CTSA (Clinical and Translational Science Award) Informatics Program.

    View details for PubMedID 20351886

  • Novel integration of hospital electronic medical records and gene expression measurements to identify genetic markers of maturation. Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Chen, D. P., Weber, S. C., Constantinou, P. S., Ferris, T. A., Lowe, H. J., Butte, A. J. 2008: 243-254

    Abstract

    Traditionally, the elucidation of genes involved in maturation and aging has been studied in a temporal fashion by examining gene expression at different time points in an organism's life as well as by knocking out, knocking in, and mutating genes thought to be involved. Here, we propose an in silico method to combine clinical electronic medical record (EMR) data and gene expression measurements in the context of disease to identify genes that may be involved in the process of human maturation and aging. First we show that absolute lymphocyte count may serve as a biomarker for maturation by using statistical methods to compare trends among different clinical laboratory tests in response to an increase in age. We then propose using the rate of decay for absolute lymphocyte count across 12 diseases as a proxy for differences in aging. We correlate the differing rates with gene expression across the same diseases to find maturation/aging related genes. Among the 53 genes with strongest correlations between expression profile and change in rate of decay, we found genes previously implicated in the process of aging, including MGMT (DNA repair), TERF2 (telomere stability), POLD1 (DNA replication and repair), and POLG (mtDNA replication).

    View details for PubMedID 18229690

  • Clinical arrays of laboratory measures, or "clinarrays", built from an electronic health record enable disease subtyping by severity. AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium Chen, D. P., Weber, S. C., Constantinou, P. S., Ferris, T. A., Lowe, H. J., Butte, A. J. 2007: 115-119

    Abstract

    The severity of diseases has often been assigned by direct observation of a patient and by pathological examination after symptoms have appeared. As we move into the genomic era, the ability to predict disease severity prior to manifestation has improved dramatically due to genomic sequencing and analysis of gene expression microarrays. However, as the severity of diseases can be exacerbated by non genetic factors, the ability to predict disease severity by examining gene expression alone may be inadequate. We propose the creation of a "clinarray" to examine phenotypic expression in the form of clinical laboratory measurements. We demonstrate that the clinarray can be used to distinguish between the severities of patients with cystic fibrosis and those with Crohn's disease by applying unsupervised clustering methods that have been previously applied to microarrays.

    View details for PubMedID 18693809

  • A proposed key escrow system for secure patient information disclosure in biomedical research databases AMIA 2002 SYMPOSIUM, PROCEEDINGS Ferris, T. A., Garrison, G. M., Lowe, H. J. 2002: 245-249

    Abstract

    Access to clinical data is of increasing importance to biomedical research. The pending HIPAA privacy regulations provide specific requirements for the release of protected health information. Under the regulations, biomedical researchers may utilize anonymized data, or adhere to HIPAA requirements regarding protected health information. In order to provide researchers with anonymized data from a clinical research database, we reviewed several published strategies for de-identification of protected health information. Critical analysis with respect to this project suggests that de-identification alone is problematic when applied to clinical research databases. We propose a hybrid system; utilizing secure key escrow, de-identification, and role-based access for IRB approved researchers.

    View details for Web of Science ID 000189418100050

    View details for PubMedID 12463824

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