Evidence map›Paper›PMID 40538131›Full record

ReviewAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

From Code to Life: The AI-Driven Revolution in Genome Editing.

Zhidong Li, Wasi Ullah Khan, Genxiang Bai, Chao Dong, Jungang Wang, Youpeng Zhang, Chong Wang, Hongbin Zhang, Wenyi Wang, Ming Luo and 1 more

Abstract readReview
In one paragraph

Review in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Artificial intelligence-driven advancements in agricultural biotechnology.Journal, genetic engineering & biotechnology · 2026
    Review
  3. Review
  4. Harnessing artificial intelligence in plant breeding: innovations in digital phenotyping and breeding methodologies.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Review
  5. Review
  6. Review
  7. Review
  8. The Potential of Cognitive-Inspired Neural Network Modeling Framework for Computer Vision.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  9. Review
  10. From Code to Life: The AI-Driven Revolution in Genome Editing.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    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

11 authors.

Zhidong LiNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.
Wasi Ullah KhanNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.
Genxiang BaiSouth China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China.
Chao DongSchool of Life Sciences, East China Normal University, Shanghai, 200241, China.
Jungang WangNational Key Laboratory for Tropical Crop Breeding, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou, 571101, China.
Youpeng ZhangNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.
Chong WangNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.
Hongbin ZhangNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.
Wenyi WangCollege of Agriculture, South China Agricultural University, Guangzhou, 510642, China.
Ming LuoSouth China Botanical Garden, Chinese Academy of Sciences, Guangzhou, 510650, China.
Fei ChenNational Key Laboratory for Tropical Crop Breeding, College of breeding and multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya, 572025, China.ORCID https://orcid.org/0000-0002-4346-6906

Funding

Guangdong Natural Science Funds for Distinguished Young Scholars 2022B1515020026Hainan Province Science and Technology Special Fund ZDYF2023XDNY050Hainan Provincial Natural Science Foundation of China 324RC452Hainan Provincial Natural Science Foundation of China 325QN234National Natural Science Foundation of China 32172614Project of National Key Laboratory for Tropical Crop Breeding NKLTCB202337South China Botanical Garden, Chinese Academy of Sciences Y2021094Youth Innovation Promotion Association, Chinese Academy of Sciences Y2021094
6 · The paper itself

Abstract

Genome editing has revolutionized modern biotechnology, enabling precise modifications to DNA sequences with far-reaching applications in medicine, agriculture, and synthetic biology. Recent advancements in artificial intelligence (AI) have significantly enhanced genome editing by improving target selection, minimizing off-target effects, and optimizing CRISPR-associated systems. AI-driven models, such as deep learning-based predictors and protein language models, enable more accurate sgRNA design, novel Cas protein discovery, and enhanced gene regulatory network analysis. Additionally, AI-powered tools facilitate large-scale data integration, accelerating functional genomics and therapeutic genome editing. This review explores the intersection of AI and genome editing, highlighting key innovations, challenges, and future prospects. Despite its transformative potential, AI-driven genome editing raises ethical concerns regarding data bias, algorithmic transparency, and unintended genetic modifications. Addressing these challenges requires interdisciplinary collaboration between AI researchers, molecular biologists, and policymakers. As AI continues to evolve, its integration with genome editing will pave the way for groundbreaking advancements in precision medicine, genetic disease treatment, and sustainable agriculture.

Indexed as

Artificial IntelligenceGene EditingCRISPR-Cas SystemsHumansartificial intelligenceCRISPRdeep learninggene regulationgenome editing

Identifiers

PMID40538131
PMCPMC12376515

What Socratic holds

Textmetadata
LicenceCC BY
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.