Evidence map›Paper›PMID 32044952›Full record

ArticleBioinformatics (Oxford, England)2020

TeSS: a platform for discovering life-science training opportunities.

Niall Beard, Finn Bacall, Aleksandra Nenadic, Milo Thurston, Carole A Goble, Susanna-Assunta Sansone, Teresa K Attwood

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% of its field
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.

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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

7 authors at 2 institutions in 1 country.

Niall BeardDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.
Finn BacallDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.
Aleksandra NenadicDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.
Milo ThurstonDepartment of Engineering Science, Oxford e-Research Centre, University of Oxford, Oxford OX1 3QG, UK.
Carole A GobleDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.
Susanna-Assunta SansoneDepartment of Engineering Science, Oxford e-Research Centre, University of Oxford, Oxford OX1 3QG, UK.
Teresa K AttwoodDepartment of Computer Science, The University of Manchester, Manchester M13 9PL, UK.
University of Manchester · GBUniversity of Oxford · GB

Funding

Biotechnology and Biological Sciences Research Council BB/L005050/1
6 · The paper itself

Abstract

summaryDispersed across the Internet is an abundance of disparate, disconnected training information, making it hard for researchers to find training opportunities that are relevant to them. To address this issue, we have developed a new platform-TeSS-which aggregates geographically distributed information and presents it in a central, feature-rich portal. Data are gathered automatically from content providers via bespoke scripts. These resources are cross-linked with related data and tools registries, and made available via a search interface, a data API and through widgets. AVAILABILITY AND IMPLEMENTATION: https://tess.elixir-europe.org.

Indexed as

Biological Science DisciplinesSoftwareHumansInternetResearch Personnel

Identifiers

PMID32044952
PMCPMC7214044
OpenAlexW3006186992

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.