Evidence map›Paper›PMID 40496817›Full record

ArticleMolecular therapy. Nucleic acids2025

Generative artificial intelligence, integrative bioinformatics, and single-cell analysis reveal Alzheimer's genetic and immune landscape.

Arpita Das, Manojit Bhattacharya, Ali Saber Abdelhameed, Sang-Soo Lee, Chiranjib Chakraborty

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Agentic AI scientists and the rise of virtual laboratories.Annals of medicine and surgery (2012) · 2026
    Article
  3. Article
  4. 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

5 authors.

Arpita DasDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126, India.
Manojit BhattacharyaDepartment of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore, Odisha 756020, India.
Ali Saber AbdelhameedDepartment of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, P.O. Box 2457, Riyadh 11451, Saudi Arabia.
Sang-Soo LeeInstitute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon, Gangwon-Do 24252, Republic of Korea.
Chiranjib ChakrabortyDepartment of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The research aims to understand Alzheimer's genetic and immune landscapes using the amalgamation of three technologies: artificial intelligence (GenAI), integrative bioinformatics, and single-cell analysis. First, the study aims to identify and characterize the significant genes associated with Alzheimer's disease (AD) using three GenAI models (GPT‑4o, Gemini model, and DeepSeek). After the genes were accumulated from GenAI models, 27 genes associated with AD were recoded. Furthermore, they were analyzed using integrative bioinformatics methods. Similarly, the immune landscape of AD using single-cell analysis was also explored, which reveals a high percentage of effector CD8

Indexed as

Alzheimer’s diseaseBioinformaticsGenAIgenetic and immune landscapesingle-cell analysis

Identifiers

PMID40496817
PMCPMC12148819

What Socratic holds

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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 Socratic graph.