Evidence map›Paper›PMID 25654371›Full record

ArticlePLoS computational biology2015

A quick guide for building a successful bioinformatics community.

Aidan Budd, Manuel Corpas, Michelle D Brazas, Jonathan C Fuller, Jeremy Goecks, Nicola J Mulder, Magali Michaut, B F Francis Ouellette, Aleksandra Pawlik, Niklas Blomberg

Abstract read
In one paragraph

Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed.

  1. Article
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  8. Article
  9. Matchmaking in Bioinformatics.F1000Research · 2018
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Aidan BuddStructural and Computational Biology (SCB) Unit, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany.
Manuel CorpasThe Genome Analysis Centre (TGAC), Norwich Research Park, Norwich, United Kingdom.
Michelle D BrazasOntario Institute for Cancer Research, MaRS Centre, West Tower, Toronto, Ontario, Canada.
Jonathan C FullerHeidelberg Institute for Theoretical Studies (HITS) gGmbH, Heidelberg, Germany.
Jeremy GoecksThe Computational Biology Institute, George Washington University, Innovation Hall, Virginia, United States of America.
Nicola J MulderComputational Biology Group, Institute of Infectious Disease and Molecular Medicine (IDM), University of Cape Town Faculty of Health Sciences, Cape Town, South Africa.
Magali MichautComputational Cancer Biology, Netherlands Cancer Institute, Amsterdam, the Netherlands.
B F Francis OuelletteOntario Institute for Cancer Research, MaRS Centre, West Tower, Toronto, Ontario, Canada; Department of Cell and Systems Biology, University of Toronto, Toronto, Canada.
Aleksandra PawlikThe Software Sustainability Institute, School of Computer Science, University of Manchester, Manchester, United Kingdom.
Niklas BlombergELIXIR Hub, Wellcome Trust Genome Campus, Cambridge, United Kingdom.

Funding

H3ABioNet: a sustainable African Bioinformatics Network for H3AfricaU41HG006941 · NHGRI · UNIVERSITY OF CAPE TOWN · PI MULDER, NICOLA · 2012 to 2017
$14.8M
Democratization of Data Analysis in Life Sciences Through GalaxyU41HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI NEKRUTENKO, ANTON, SCHATZ, MICHAEL · 2012 to 2020
$14.4M
Democratization of Data Analysis in Life Sciences Through GalaxyU24HG006620 · NHGRI · PENNSYLVANIA STATE UNIVERSITY, THE · PI Daniel James Blankenberg, Jeremy Goecks · 2021 to 2026
$9.8M
Dynamically scalable accessible analysis for next generation sequence dataRC2HG005542 · NHGRI · EMORY UNIVERSITY · PI NEKRUTENKO, ANTON, TAYLOR, JAMES PETER · 2009 to 2010
$1.5M
A Turnkey Solution for Next Generation Sequence Data AnalysisR21HG005133 · NHGRI · EMORY UNIVERSITY · PI TAYLOR, JAMES PETER · 2009 to 2010
$445k
Biotechnology and Biological Sciences Research CouncilNHGRI NIH HHS HG005133NHGRI NIH HHS HG005542NHGRI NIH HHS HG006620NHGRI NIH HHS R21 HG005133NHGRI NIH HHS RC2 HG005542NHGRI NIH HHS U24 HG006620NHGRI NIH HHS U41 HG006620NHGRI NIH HHS U41 HG006941NHGRI NIH HHS U41HG006941
6 · The paper itself

Abstract

"Scientific community" refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop "The 'How To Guide' for Establishing a Successful Bioinformatics Network" at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB).

Indexed as

CommunicationComputational BiologyHumansInternetSocial Media

Identifiers

PMID25654371
PMCPMC4318577

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.