Evidence map›Paper›PMID 25202745›Full record

ArticleTheScientificWorldJournal2014

Database constraints applied to metabolic pathway reconstruction tools.

Jordi Vilaplana, Francesc Solsona, Ivan Teixido, Anabel Usié, Hiren Karathia, Rui Alves, Jordi Mateo

Abstract read
In one paragraph

Article in TheScientificWorldJournal, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Jordi VilaplanaComputer Science Department & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain.
Francesc SolsonaComputer Science Department & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain.
Ivan TeixidoComputer Science Department & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain.
Anabel UsiéCEBAL, IPBeja Campus, 7800 Beja, Portugal.
Hiren KarathiaDepartment of Basic Medical Sciences & IRBLleida, Edifici Recerca Biomedica I, Universitat de Lleida, Avenida Rovira Roure 80, 25198 Lleida, Spain.
Rui AlvesDepartment of Basic Medical Sciences & IRBLleida, Edifici Recerca Biomedica I, Universitat de Lleida, Avenida Rovira Roure 80, 25198 Lleida, Spain.
Jordi MateoComputer Science Department & INSPIRES, University of Lleida, Jaume II 69, 25001 Lleida, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our group developed two biological applications, Biblio-MetReS and Homol-MetReS, accessing the same database of organisms with annotated genes. Biblio-MetReS is a data-mining application that facilitates the reconstruction of molecular networks based on automated text-mining analysis of published scientific literature. Homol-MetReS allows functional (re)annotation of proteomes, to properly identify both the individual proteins involved in the process(es) of interest and their function. It also enables the sets of proteins involved in the process(es) in different organisms to be compared directly. The efficiency of these biological applications is directly related to the design of the shared database. We classified and analyzed the different kinds of access to the database. Based on this study, we tried to adjust and tune the configurable parameters of the database server to reach the best performance of the communication data link to/from the database system. Different database technologies were analyzed. We started the study with a public relational SQL database, MySQL. Then, the same database was implemented by a MapReduce-based database named HBase. The results indicated that the standard configuration of MySQL gives an acceptable performance for low or medium size databases. Nevertheless, tuning database parameters can greatly improve the performance and lead to very competitive runtimes.

Indexed as

Databases, GeneticMetabolic Networks and PathwaysSoftwareComputational BiologyModels, Biological

Identifiers

PMID25202745
PMCPMC4151372

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.