ArticleJournal of personalized medicine2015
Phenotype-Driven Plasma Biobanking Strategies and Methods.
Article in Journal of personalized medicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05277116 (The Electronic Medical Records and GEnomics), which is not on this map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
The Electronic Medical Records and GEnomics (eMERGE) Network Genomic Risk Assessment
Who cites it
10 citing papers in PubMed.
- Prevalence and Clinical Impact of Pathogenic Variants in Cardiomyopathy Genes Among Individuals with Cardiac Conduction Disorders.medRxiv : the preprint server for health sciences · 2026Article
- Revealing polygenic pleiotropy using genetic risk scores for asthma.HGG advances · 2023Article
- Global Biobank analyses provide lessons for developing polygenic risk scores across diverse cohorts.Cell genomics · 2023Article
- High-throughput phenotyping with temporal sequences.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Each patient is a research biorepository: informatics-enabled research on surplus clinical specimens via the living BioBank.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Harnessing the potential of blood donation archives for influenza surveillance and control.PloS one · 2020Article
- Accelerating Biomarker Discovery Through Electronic Health Records, Automated Biobanking, and Proteomics.Journal of the American College of Cardiology · 2019Article
- Integration of complex data sources to provide biologic insight into pulmonary vascular disease (2015 Grover Conference Series).Pulmonary circulation · 2016Review
- Targeting the untargeted in molecular phenomics with structurally-selective ion mobility-mass spectrometry.Current opinion in biotechnology · 2016Review
- Text Mining for Precision Medicine: Bringing Structure to EHRs and Biomedical Literature to Understand Genes and Health.Advances in experimental medicine and biology · 2016Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors.
Funding
Abstract
Biobank development and integration with clinical data from electronic medical record (EMR) databases have enabled recent strides in genomic research and personalized medicine. BioVU, Vanderbilt's DNA biorepository linked to de-identified clinical EMRs, has proven fruitful in its capacity to extensively appeal to numerous areas of biomedical and clinical research, supporting the discovery of genotype-phenotype interactions. Expanding on experiences in BioVU creation and development, we have recently embarked on a parallel effort to collect plasma in addition to DNA from blood specimens leftover after routine clinical testing at Vanderbilt. This initiative offers expanded utility of BioVU by combining proteomic and metabolomic approaches with genomics and/or clinical outcomes, widening the breadth for potential research and subsequent future impact on clinical care. Here, we describe the considerations and components involved in implementing a plasma biobank program from a feasibility assessment through pilot sample collection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.