Evidence map›Paper›PMID 30258892›Full record

ArticleGenes & diseases2016

Computational identification and analysis of neurodegenerative disease associated protein kinases in hominid genomes.

Saranya Jayapalan, Devika Subramanian, Jeyakumar Natarajan

Open access · diamondAbstract read
In one paragraph

Article in Genes & diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 26% 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

5 citing papers in PubMed, 15 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Saranya JayapalanData Mining and Text Mining Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, India.
Devika SubramanianData Mining and Text Mining Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, India.
Jeyakumar NatarajanData Mining and Text Mining Lab, Department of Bioinformatics, Bharathiar University, Coimbatore, India.
Bharathiar University · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein kinases play an important role in the incidence of neurodegenerative diseases. However their incidence in non-human primates is found to be very low. Small differences among the genomes might influence the disease susceptibilities. The present study deals with finding the genetic differences of protein kinases in humans and their three closest evolutionary partners chimpanzee, gorilla and orangutan for three neurodegenerative diseases namely, Alzheimer's, Parkinson's and Huntington's diseases. In total 47 human protein kinases associated with three neurodegenerative diseases and their orthologs from other three non-human primates were identified and analyzed for any possible susceptibility factors in humans. Multiple sequence alignment and pairwise sequence alignment revealed that, 18 human protein kinases including DYRK1A, RPS6KB1, and GRK6 contained significant indels and substitutions. Further phosphorylation site analysis revealed that eight kinases including MARK2 and LTK contained sites of phosphorylation exclusive to human genomes which could be particular candidates in determining disease susceptibility between human and non-human primates. Final pathway analysis of these eight kinases and their targets revealed that these kinases could have long range consequences in important signaling pathways which are associated with neurodegenerative diseases.

Indexed as

HominidsInteraction analysisNeurodegenerative diseasesPhosphorylation sitesProtein kinases

Identifiers

PMID30258892
PMCPMC6147167
OpenAlexW2335920381

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.