ArticleBMC bioinformatics2015
An automated real-time integration and interoperability framework for bioinformatics.
Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- TASKA: A modular task management system to support health research studies.BMC medical informatics and decision making · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIn recent years data integration has become an everyday undertaking for life sciences researchers. Aggregating and processing data from disparate sources, whether through specific developed software or via manual processes, is a common task for scientists. However, the scope and usability of the majority of current integration tools fail to deal with the fast growing and highly dynamic nature of biomedical data.
resultsIn this work we introduce a reactive and event-driven framework that simplifies real-time data integration and interoperability. This platform facilitates otherwise difficult tasks, such as connecting heterogeneous services, indexing, linking and transferring data from distinct resources, or subscribing to notifications regarding the timeliness of dynamic data. For developers, the framework automates the deployment of integrative and interoperable bioinformatics applications, using atomic data storage for content change detection, and enabling agent-based intelligent extract, transform and load tasks.
conclusionsThis work bridges the gap between the growing number of services, accessing specific data sources or algorithms, and the growing number of users, performing simple integration tasks on a recurring basis, through a streamlined workspace available to researchers and developers alike.
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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.