Evidence map›Paper›PMID 38549639›Full record

ArticleJournal of Alzheimer's disease reports2024

Intelligent Alzheimer's Diseases Gene Association Prediction Model Using Deep Regulatory Genomic Neural Networks.

M Rohini, S Oswalt Manoj, D Surendran

Open access · diamondAbstract read
In one paragraph

Article in Journal of Alzheimer's disease reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 38% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

M RohiniDepartment of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
S Oswalt ManojDepartment of Computer Science and Engineering, Sri Krishna College of Engineering and Technology, Coimbatore, India.
D SurendranDepartment of Information Technology, Karpagam College of Engineering, Coimbatore, India.
Karpagam Academy of Higher Education · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alzheimer's disease (AD) is an illness that affects the nervous system, leading to a loss in cognitive and logical abilities. Gene regulatory expressions, which are the complex language exhibited by DNA, serve several functionalities, including the physical and biological life cycle processes in the human body. The gene expression sequence affects the pathology experienced by an individual, its longevity, and potential for a cure. The transcription factors, from DNA to RNA conversion, and the binding process determine the gene expression, which varies for every human organ and disease. This study proposes Deep convolutional neural network model that reads the gene regulatory expression sequence through various convolutional layers encoded to detect positive spikes in transcription factors. This results in the prediction of disease conversion probability from mild cognitive impairment to AD which is the key-requisite for affected geriatric cohorts.

Indexed as

Alzheimer’s diseaseAPOEDNAgene regulatory mechanismrs429358rs7412

Identifiers

PMID38549639
PMCPMC10977432
OpenAlexW4392845605

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.