Evidence map›Paper›PMID 31007525›Full record

ArticleEvolutionary bioinformatics online2019

Genome-Wide Search for Tyrosine Phosphatases in the Human Genome Through Computational Approaches Leads to the Discovery of Few New Domain Architectures.

Teerna Bhattacharyya, Ramanathan Sowdhamini

Open access · goldAbstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 45% of its field
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 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Genomic Survey of Tyrosine Kinases Repertoire inEvolutionary bioinformatics online · 2020
    Article
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 at 1 institution in 1 country.

Teerna BhattacharyyaNational Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.
Ramanathan SowdhaminiNational Centre for Biological Sciences, Tata Institute of Fundamental Research, Bangalore, India.ORCID https://orcid.org/0000-0002-6642-2367
Tata Institute of Fundamental Research · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reversible phosphorylation maintained by protein kinases and phosphatases is an integral part of intracellular signalling, and phosphorylation on tyrosine is extensively utilised in higher eukaryotes. Tyrosine phosphatases are enzymes that not only scavenge phosphotyrosine but are also involved in wide range of signalling pathways. As a result, mutations in these enzymes have been implicated in the pathogenesis of several diseases like cancer, autoimmune disorders, and muscle-related diseases. The genes that harbour phosphatase domain also display diversity in co-existing domains suggesting the recruitment of the catalytic machinery in diverse pathways. We have examined the current draft of the human genome, using a combination of 3 sequence search methods and validations, and identified 101 genes encoding tyrosine phosphatase-containing gene products, agreeing with previous reports. Such gene products adopt 37 unique domain architectures (DAs), including few new ones and harbouring few co-existing domains that have not been reported before. This semi-automated computational approach for detection of gene products belonging to a particular superfamily can now be easily applied at whole genome level on other mammalian genomes and for other protein domains as well.

Indexed as

cell signallingdephosphorylationprotein superfamilyputative domainssequence search algorithms

Identifiers

PMID31007525
PMCPMC6457024
OpenAlexW2936915885

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.