Evidence map›Paper›PMID 18445632›Full record

ArticleNucleic acids research2008

High-throughput functional annotation and data mining with the Blast2GO suite.

Stefan Götz, Juan Miguel García-Gómez, Javier Terol, Tim D Williams, Shivashankar H Nagaraj, María José Nueda, Montserrat Robles, Manuel Talón, Joaquín Dopazo, Ana Conesa

Abstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2,363 papers.

0numbers the graph read from it
0cells of the map it votes in
2,363citing 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

2,363 citing papers in PubMed.

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2,303 more citing papers are in PubMed but not listed here.

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.

Stefan GötzBioinformatics Department, Centro de Investigación Principe Felipe, Valencia, Spain.
Juan Miguel García-Gómez
Javier Terol
Tim D Williams
Shivashankar H Nagaraj
María José Nueda
Montserrat Robles
Manuel Talón
Joaquín Dopazo
Ana Conesa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional genomics technologies have been widely adopted in the biological research of both model and non-model species. An efficient functional annotation of DNA or protein sequences is a major requirement for the successful application of these approaches as functional information on gene products is often the key to the interpretation of experimental results. Therefore, there is an increasing need for bioinformatics resources which are able to cope with large amount of sequence data, produce valuable annotation results and are easily accessible to laboratories where functional genomics projects are being undertaken. We present the Blast2GO suite as an integrated and biologist-oriented solution for the high-throughput and automatic functional annotation of DNA or protein sequences based on the Gene Ontology vocabulary. The most outstanding Blast2GO features are: (i) the combination of various annotation strategies and tools controlling type and intensity of annotation, (ii) the numerous graphical features such as the interactive GO-graph visualization for gene-set function profiling or descriptive charts, (iii) the general sequence management features and (iv) high-throughput capabilities. We used the Blast2GO framework to carry out a detailed analysis of annotation behaviour through homology transfer and its impact in functional genomics research. Our aim is to offer biologists useful information to take into account when addressing the task of functionally characterizing their sequence data.

Indexed as

GenomicsSequence Analysis, DNASequence Analysis, ProteinSoftwareAnimalsComputational BiologyComputer GraphicsDatabases, GeneticExpressed Sequence TagsGenesVocabulary, Controlled

Identifiers

PMID18445632
PMCPMC2425479

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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.