Evidence map›Paper›PMID 19923227›Full record

ArticleNucleic acids research2010

FunSimMat update: new features for exploring functional similarity.

Andreas Schlicker, Mario Albrecht

Abstract read
In one paragraph

Article in Nucleic acids research, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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

16 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  10. Drug-target interaction prediction by integrating chemical, genomic, functional and pharmacological data.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2014
    Article
  11. Chapter 15: disease gene prioritization.PLoS computational biology · 2013
    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

2 authors.

Andreas SchlickerMax Planck Institute for Informatics, Campus E1.4, 66123 Saarbrücken, Germany. andreas.schlicker@mpi-inf.mpg.de
Mario Albrecht

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantifying the functional similarity of genes and their products based on Gene Ontology annotation is an important tool for diverse applications like the analysis of gene expression data, the prediction and validation of protein functions and interactions, and the prioritization of disease genes. The Functional Similarity Matrix (FunSimMat, http://www.funsimmat.de) is a comprehensive database providing various precomputed functional similarity values for proteins in UniProtKB and for protein families in Pfam and SMART. With this update, we significantly increase the coverage of FunSimMat by adding data from the Gene Ontology Annotation project as well as new functional similarity measures. The applicability of the database is greatly extended by the implementation of a new Gene Ontology-based method for disease gene prioritization. Two new visualization tools allow an interactive analysis of the functional relationships between proteins or protein families. This is enhanced further by the introduction of an automatically derived hierarchy of annotation classes. Additional changes include a revised user front-end and a new RESTlike interface for improving the user-friendliness and online accessibility of FunSimMat.

Indexed as

Databases, GeneticDatabases, Nucleic AcidAnimalsComputational BiologyDatabases, ProteinGene Expression ProfilingHumansInformation Storage and RetrievalInternetProtein Interaction MappingProteinsProtein Structure, TertiarySoftwareUser-Computer InterfaceVocabulary, ControlledProteins

Identifiers

PMID19923227
PMCPMC2808991

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.