Evidence map›Paper›PMID 30582061›Full record

ArticleHeliyon2018

Training bioinformaticians in High Performance Computing.

Esteban Pérez-Wohlfeil, Oscar Torreno, Louisa J Bellis, Pedro L Fernandes, Brane Leskosek, Oswaldo Trelles

Abstract read
In one paragraph

Article in Heliyon, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

6 authors.

Esteban Pérez-WohlfeilComputer Architecture Department, University of Malaga, Malaga, Spain.
Oscar TorrenoComputer Architecture Department, University of Malaga, Malaga, Spain.
Louisa J BellisDepartment of Genetics, University of Cambridge, Cambridge, United Kingdom.
Pedro L FernandesInstituto Gulbenkian de Ciência, Oeiras, Portugal.
Brane LeskosekUniversity of Ljubljana, Faculty of Medicine, Institute for Biostatistics and Medical Informatics, Ljubljana, Slovenia.
Oswaldo TrellesComputer Architecture Department, University of Malaga, Malaga, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last decade, bioinformatics has become an indispensable branch of modern science research, experiencing an explosion in financial support, developed applications and data collection. The growth of the datasets that are emerging from research laboratories, industry, the health sector, etc., are increasingly raising the levels of demand in computing power and storage. Processing biological data, in the large scales of these datasets, often requires the use of High Performance Computing (HPC) resources, especially when dealing with certain types of omics data, such as genomic and metagenomic data. Such computational resources not only require substantial investments, but they also involve high maintenance costs. More importantly, in order to keep good returns from the investments, specific training needs to be put in place to ensure that wasting is minimized. Furthermore, given that bioinformatics is a highly interdisciplinary field where several other domains intersect (such as biology, chemistry, physics and computer science), researchers from these areas also require bioinformatics-specific training in HPC, in order to fully take advantage of supercomputing centers. In this document, we describe our experience in training researchers from several different disciplines in HPC, as applied to bioinformatics under the framework of the leading European bioinformatics platform ELIXIR, and analyze both the content and outcomes of the course.

Indexed as

BioinformaticsComputational biologyComputer scienceEducation

Identifiers

PMID30582061
PMCPMC6299036

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.