Evidence map›Paper›PMID 17724062›Full record

ArticleBioinformatics (Oxford, England)2007

TMpro web server and web service: transmembrane helix prediction through amino acid property analysis.

Madhavi Ganapathiraju, Christopher Jon Jursa, Hassan A Karimi, Judith Klein-Seetharaman

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

4 authors.

Madhavi GanapathirajuLanguage Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
Christopher Jon Jursa
Hassan A Karimi
Judith Klein-Seetharaman

Funding

Bridging Sequence Patterns and Structural DynamicsR01LM007994 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI BAHAR, IVET · 2004 to 2011
$3.0M
NLM NIH HHS R01 LM007994
6 · The paper itself

Abstract

unlabelledTMpro is a transmembrane (TM) helix prediction algorithm that uses language processing methodology for TM segment identification. It is primarily based on the analysis of statistical distributions of properties of amino acids in transmembrane segments. This article describes the availability of TMpro on the internet via a web interface. The key features of the interface are: (i) output is generated in multiple formats including a user-interactive graphical chart which allows comparison of TMpro predicted segment locations with other labeled segments input by the user, such as predictions from other methods. (ii) Up to 5000 sequences can be submitted at a time for prediction. (iii) TMpro is available as a web server and is published as a web service so that the method can be accessed by users as well as other services depending on the need for data integration. AVAILABILITY: http://linzer.blm.cs.cmu.edu/tmpro/ (web server and help), http://blm.sis.pitt.edu:8080/axis/services/TMProFetcherService (web service).

Indexed as

InternetModels, ChemicalModels, MolecularSoftwareUser-Computer InterfaceComputer SimulationMembrane ProteinsProtein ConformationSequence Analysis, ProteinMembrane Proteins

Identifiers

PMID17724062
PMCPMC3263380

What OpenQuestion holds

Textmetadata
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.