ArticleBriefings in bioinformatics2009
Bringing Web 2.0 to bioinformatics.
Article in Briefings in bioinformatics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- GEM-NET: Lessons in Multi-Institution Teamwork Using Collaboration Software.ACS central science · 2019Article
- A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.PloS one · 2015Article
- LncRNAWiki: harnessing community knowledge in collaborative curation of human long non-coding RNAs.Nucleic acids research · 2015Article
- RiceWiki: a wiki-based database for community curation of rice genes.Nucleic acids research · 2014Article
- Community intelligence in knowledge curation: an application to managing scientific nomenclature.PloS one · 2013Article
- Bioinformatics clouds for big data manipulation.Biology direct · 2012Review
- ABrowse--a customizable next-generation genome browser framework.BMC bioinformatics · 2012Article
- ImageJS: Personalized, participated, pervasive, and reproducible image bioinformatics in the web browser.Journal of pathology informatics · 2012Article
- Booly: a new data integration platform.BMC bioinformatics · 2010Article
- The filamentous fungal gene expression database (FFGED).Fungal genetics and biology : FG & B · 2010Article
- Current trends and new challenges of databases and web applications for systems driven biological research.Frontiers in physiology · 2010Article
- Pathway projector: web-based zoomable pathway browser using KEGG atlas and Google Maps API.PloS one · 2009Article
- A web server for interactive and zoomable Chaos Game Representation images.Source code for biology and medicine · 2009Article
- WhichGenes: a web-based tool for gathering, building, storing and exporting gene sets with application in gene set enrichment analysis.Nucleic acids research · 2009Article
- Genome Projector: zoomable genome map with multiple views.BMC bioinformatics · 2009Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Enabling deft data integration from numerous, voluminous and heterogeneous data sources is a major bioinformatic challenge. Several approaches have been proposed to address this challenge, including data warehousing and federated databasing. Yet despite the rise of these approaches, integration of data from multiple sources remains problematic and toilsome. These two approaches follow a user-to-computer communication model for data exchange, and do not facilitate a broader concept of data sharing or collaboration among users. In this report, we discuss the potential of Web 2.0 technologies to transcend this model and enhance bioinformatics research. We propose a Web 2.0-based Scientific Social Community (SSC) model for the implementation of these technologies. By establishing a social, collective and collaborative platform for data creation, sharing and integration, we promote a web services-based pipeline featuring web services for computer-to-computer data exchange as users add value. This pipeline aims to simplify data integration and creation, to realize automatic analysis, and to facilitate reuse and sharing of data. SSC can foster collaboration and harness collective intelligence to create and discover new knowledge. In addition to its research potential, we also describe its potential role as an e-learning platform in education. We discuss lessons from information technology, predict the next generation of Web (Web 3.0), and describe its potential impact on the future of bioinformatics studies.
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.