Evidence map›Paper›PMID 22962467›Full record

ArticleBioinformatics (Oxford, England)2012

LocTree2 predicts localization for all domains of life.

Tatyana Goldberg, Tobias Hamp, Burkhard Rost

Abstract readValidation Study
In one paragraph

Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.

0numbers the graph read from it
0cells of the map it votes in
57citing 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

57 citing papers in PubMed.

  1. Single-Cell Protein Assays in Context: From 2D to 3D and In Situ Analysis.Annual review of analytical chemistry (Palo Alto, Calif.) · 2026
    Review
  2. Article
  3. Protein subcellular localization prediction tools.Computational and structural biotechnology journal · 2024
    Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Protein Sorting Prediction.Methods in molecular biology (Clifton, N.J.) · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Review
  17. Article
  18. Computational methods for protein localization prediction.Computational and structural biotechnology journal · 2021
    Review
  19. Article
  20. Review
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

3 authors.

Tatyana GoldbergTUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany. localization@rostlab.org
Tobias Hamp
Burkhard Rost

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationSubcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled.

resultsIn this study, we introduced a framework to predict localization in life's three domains, including globular and membrane proteins (3 classes for archaea; 6 for bacteria and 18 for eukaryota). The resulting method, LocTree2, works well even for protein fragments. It uses a hierarchical system of support vector machines that imitates the cascading mechanism of cellular sorting. The method reaches high levels of sustained performance (eukaryota: Q18=65%, bacteria: Q6=84%). LocTree2 also accurately distinguishes membrane and non-membrane proteins. In our hands, it compared favorably with top methods when tested on new data. AVAILABILITY: Online through PredictProtein (predictprotein.org); as standalone version at http://www.rostlab.org/services/loctree2. CONTACT: localization@rostlab.org SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Indexed as

Support Vector MachineAnimalsArchaeal ProteinsBacterial ProteinsMembrane ProteinsMolecular Sequence AnnotationProteinsSequence Analysis, ProteinArchaeal ProteinsBacterial ProteinsMembrane ProteinsProteins

Identifiers

PMID22962467
PMCPMC3436817

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Registered trials

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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.