Evidence map›Paper›PMID 19900966›Full record

ArticleNucleic acids research2010

The MiST2 database: a comprehensive genomics resource on microbial signal transduction.

Luke E Ulrich, Igor B Zhulin

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 168 papers.

0numbers the graph read from it
0cells of the map it votes in
168citing 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

168 citing papers in PubMed.

  1. Article
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  4. Review
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  10. Microbial Genomics: Innovative Targets and Mechanisms.Antibiotics (Basel, Switzerland) · 2023
    Review
  11. Article
  12. Article
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  15. Article
  16. Review
  17. Article
  18. Research progress on two-component signal transduction systems inHua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2021
    Review
  19. Article
  20. Article

108 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

2 authors.

Luke E UlrichAgile Genomics LLC, Mount Pleasant, SC 29466, USA. ulrich.luke+sci@gmail.com
Igor B Zhulin

Funding

Computational Genomics of Signal TransductionR01GM072285 · NIGMS · UNIVERSITY OF TENNESSEE KNOXVILLE · PI JOULINE, IGOR B. · 2004 to 2018
$3.2M
Integrating microbial signal transduction pathways and their metabolic targetsR43GM083177 · NIGMS · AGILE GENOMICS, LLC · PI ULRICH, LUKE E. · 2008 to 2008
$100k
NIGMS NIH HHS GM083177NIGMS NIH HHS GM72285NIGMS NIH HHS R01 GM072285NIGMS NIH HHS R43 GM083177
6 · The paper itself

Abstract

The MiST2 database (http://mistdb.com) identifies and catalogs the repertoire of signal transduction proteins in microbial genomes. Signal transduction systems regulate the majority of cellular activities including the metabolism, development, host-recognition, biofilm production, virulence, and antibiotic resistance of human pathogens. Thus, knowledge of the proteins and interactions that comprise these communication networks is an essential component to furthering biomedical discovery. These are identified by searching protein sequences for specific domain profiles that implicate a protein in signal transduction. Compared to the previous version of the database, MiST2 contains a host of new features and improvements including the following: draft genomes; extracytoplasmic function (ECF) sigma factor protein identification; enhanced classification of signaling proteins; novel, high-quality domain models for identifying histidine kinases and response regulators; neighboring two-component genes; gene cart; better search capabilities; enhanced taxonomy browser; advanced genome browser; and a modern, biologist-friendly web interface. MiST2 currently contains 966 complete and 157 draft bacterial and archaeal genomes, which collectively contain more than 245 000 signal transduction proteins. The majority (66%) of these are one-component systems, followed by two-component proteins (26%), chemotaxis (6%), and finally ECF factors (2%).

Indexed as

Databases, GeneticSignal TransductionArchaeaArchaeal ProteinsBacteriaBacterial ProteinsComputational BiologyDatabases, ProteinGenome, ArchaealGenome, BacterialInformation Storage and RetrievalInternetProtein Structure, TertiarySoftwareArchaeal ProteinsBacterial Proteins

Identifiers

PMID19900966
PMCPMC2808908

What OpenQuestion holds

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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.