Evidence map›Paper›PMID 41630802›Full record

ArticleEvolutionary bioinformatics online2026

Adaptive Evolution-Inspired Algorithm for Intrusion Detection in Bioinformatics Systems.

Mehtab Alam, Chandra Kanta Samal, Ashraf Ali, Abdullah Alourani

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Evolutionary bioinformatics online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Mehtab AlamDepartment of Computer Science, Acharya Narendra Dev College, University of Delhi, Delhi, India.ORCID https://orcid.org/0000-0001-7554-2160
Chandra Kanta SamalDepartment of Computer Science, Acharya Narendra Dev College, University of Delhi, Delhi, India.ORCID https://orcid.org/0000-0003-1862-5976
Ashraf AliFaculty of Computer Studies, Arab Open University, A'ali, Bahrain.
Abdullah AlouraniDepartment of Management Information Systems, College of Business and Economics, Qassim University, Buraydah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The increasing integration of bioinformatics with cloud infrastructure, artificial intelligence, and real-time data analytics has introduced unprecedented cybersecurity challenges. Sensitive genomic and clinical data, when exposed to evolving cyber threats such as data exfiltration, injection attacks, and model poisoning, require more adaptive and resilient defense mechanisms. This research presents an

Indexed as

artificial immune systembioinformaticscybersecuritydetection frameworkevolutionary algorithmsgenetic algorithmgenomic data protectionhealthcare information securityintrusion detection systemsreinforcement learningthreat drift

Identifiers

PMID41630802
PMCPMC12861380

What OpenQuestion holds

Textmetadata
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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.