Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions

This paper offers a comprehensive review of the synergy between artificial intelligence and DNA methylation analysis, encompassing machine learning, deep learning, natural language processing, and explainable artificial intelligence. In this study, we also highlighted the underexplored potential of signal processing and large language models-based models in DNA methylation research. Additionally, we discussed the challenges and limitations faced when managing and analyzing large and complex DNA methylation datasets. Furthermore, this article tries to shed light on the continuing evolution of this field and on the possible directions for future research.

Authors

Institutions

Publication Details

Journal
Briefings in Bioinformatics
Published
2025-08-31
DOI
https://doi.org/10.1093/bib/bbaf468
Citations
3
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
7.44
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions

Noura Aherrahrou, Hamid Tairi, Mohamed Adnane Mahraz, Aymane Aghziel
3 citations
Briefings in Bioinformatics
Topic Modeling
7.44
article

Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions

Noura Aherrahrou, Hamid Tairi, Mohamed Adnane Mahraz, Aymane Aghziel
article en
3 citations

Abstract

This paper offers a comprehensive review of the synergy between artificial intelligence and DNA methylation analysis, encompassing machine learning, deep learning, natural language processing, and explainable artificial intelligence. In this study, we also highlighted the underexplored potential of signal processing and large language models-based models in DNA methylation research. Additionally, we discussed the challenges and limitations faced when managing and analyzing large and complex DNA methylation datasets. Furthermore, this article tries to shed light on the continuing evolution of this field and on the possible directions for future research.

Briefings in BioinformaticsVol. 26(5)
Sidi Mohamed Ben Abdellah University (MA)
Openalex Percentile: Top 3%
Topic Modeling
7.44
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Artificial intelligence for comprehensive DNA methylation analysis: overview, challenges, and future directions — Noura Aherrahrou, Hamid Tairi, et al. · Briefings in Bioinformatics (2025) | TGRS Research Map | TGRS