Evidence map›Paper›PMID 31621694›Full record

ArticleCancer informatics2019

In Silico Genetics Revealing 5 Mutations in

Mujahed I Mustafa, Zainab O Mohammed, Naseem S Murshed, Nafisa M Elfadol, Abdelrahman H Abdelmoneim, Mohamed A Hassan

Open access · goldAbstract read
In one paragraph

Article in Cancer informatics, 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
0.7field-weighted citation impact, top 24% 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, 9 citations in OpenAlex.

  1. Article
  2. 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

6 authors at 2 institutions in 1 country.

Mujahed I MustafaDepartment of Biotechnology, Africa City of Technology, Khartoum North, Sudan.ORCID https://orcid.org/0000-0001-6893-0536
Zainab O MohammedDepartment of Haematology, Ribat University Hospital, Khartoum, Sudan.
Naseem S MurshedDepartment of Biotechnology, Africa City of Technology, Khartoum North, Sudan.
Nafisa M ElfadolDepartment of Biotechnology, Africa City of Technology, Khartoum North, Sudan.
Abdelrahman H AbdelmoneimDepartment of Biotechnology, Africa City of Technology, Khartoum North, Sudan.
Mohamed A HassanDepartment of Biotechnology, Africa City of Technology, Khartoum North, Sudan.
University of Garden City · SDNational Ribat University · SD

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAcute myeloid leukemia (AML) is an extremely heterogeneous malignant disorder; AML has been reported as one of the main causes of death in children. The objective of this work was to classify the most deleterious mutation in CCAAT/enhancer-binding protein-alpha (

methodsThe single nucleotide polymorphisms (SNPs) were claimed from the National Center for Biotechnology Information (NCBI) database and then submitted into various functional analysis tools, which were done to predict the influence of each SNP, followed by structural analysis of modeled protein followed by predicting the mutation effect on energy stability; the most damaging mutations were chosen for additional investigation by Mutation3D, Project hope, ConSurf, BioEdit, and UCSF Chimera tools.

resultsA total of 5 mutations out of 248 were likely to be responsible for the structural and functional variations in CEBPA protein, whereas in the 3'-untranslated region (3'-UTR) the result showed that among 350 SNPs in the 3'-UTR of

conclusionsIn this study, the impact of functional mutations in the CEBPA gene was investigated through different bioinformatics analysis techniques, which determined that R339W, R288P, N292S, N292T, and D63N are pathogenic mutations that have a possible functional and structural influence, therefore, could be used as genetic biomarkers and may assist in genetic studies with a special consideration of the large heterogeneity of AML.

Indexed as

Acute myeloid leukemiabioinformatics analysisCEBPAgenetic biomarkersmalignant disease

Identifiers

PMID31621694
PMCPMC6777061
OpenAlexW2969647405

What OpenQuestion holds

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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.