Isabl Platform, a digital biobank for processing multimodal patient data

The widespread adoption of high throughput technologies has democratized data generation. However, data processing in accordance with best practices remains challenging and the data capital often becomes siloed. This presents an opportunity to consolidate data assets into digital biobanks-ecosystems...

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Bibliographic Details
Published in:BMC bioinformatics 2020-11, Vol.21 (1), p.549-549, Article 549
Main Authors: Medina-Martínez, Juan S, Arango-Ossa, Juan E, Levine, Max F, Zhou, Yangyu, Gundem, Gunes, Kung, Andrew L, Papaemmanuil, Elli
Format: Article
Language:English
Subjects:
Analysis information management system
Applications programs
Artificial intelligence
Automation
Biological Specimen Banks
Catalysts
Data entry
Data processing
Databases, Factual
Evaluation
Genomics
Humans
Image processing
Information management
Internet
Methods
Multimodal user interfaces (Computers)
Next generation sequencing
Ontology
Relational data bases
Reproducibility of Results
Software
Software engineering
User-Computer Interface
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Summary:The widespread adoption of high throughput technologies has democratized data generation. However, data processing in accordance with best practices remains challenging and the data capital often becomes siloed. This presents an opportunity to consolidate data assets into digital biobanks-ecosystems of readily accessible, structured, and annotated datasets that can be dynamically queried and analysed. We present Isabl, a customizable plug-and-play platform for the processing of multimodal patient-centric data. Isabl's architecture consists of a relational database (Isabl DB), a command line client (Isabl CLI), a RESTful API (Isabl API) and a frontend web application (Isabl Web). Isabl supports automated deployment of user-validated pipelines across the entire data capital. A full audit trail is maintained to secure data provenance, governance and ensuring reproducibility of findings. As a digital biobank, Isabl supports continuous data utilization and automated meta analyses at scale, and serves as a catalyst for research innovation, new discoveries, and clinical translation.
ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-020-03879-7