Special Issue

Artificial Intelligence in Genomics: Transforming Genetic Research and Personalized Medicine

Submission Deadline: October 31, 2026 (Open) Submit Now

Guest Editor

Eric Galván-Tejada, PhD

Universidad Autónoma de Zacatecas, Zacatecas, Mexico

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Research Interests: Artificial intelligence; context computing; bioinformatics; biomedical; signal processing

Co-Editors

Karen E. Villagrana-Bañuelos, PhD

Universidad Autónoma de Zacatecas, Zacatecas, Mexico

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Research Interests: Biomedical; bioinformatics; public health

Antonio García-Domínguez, PhD

Universidad Autónoma de Zacatecas, Zacatecas, Mexico

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Research Interests: Artificial intelligence; machine learning; data science; synthetic data

Gloria Viviana Cerrillo-Rojas, PhD

Instituto Politécnico Nacional, Zacatecas, México

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Research Interests: Bioinformatic; biotechnology; molecular biology; genetics

About This Topic

This special issue mainly explores how artificial intelligence (AI) is driving the development of genomics, especially its applications in genetic research and personalized medicine. It focuses on the potential of artificial intelligence for analyzing large-scale genomic data, predicting disease risks, and optimizing gene editing technologies, as well as other applications. It also explores the challenges faced by the combination of AI and genomic science.

Keywords

Artificial intelligence (AI); genomics; genetic research; genomic data analysis; machine learning; personalized medicine

Manuscript Submission Information

Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (genetics@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.

Welcome your submission!

Publication

Open Access Original Research Predicting Tumor Mutational Burden in Prostate Cancer Using Deep Learning on Histopathological Images by Tekin Ahmet Serel  , Onur Ertunç  , Merve Meryem Kıran  , Esra Şengül  , Zeynep Ruken Hakkoymaz  and Eda Uysal Aydın Received: 11 February 2026;  Published: 07 September 2026;  doi: 10.21926/obm.genet.2603357 Abstract Tumor mutational burden (TMB) is a critical biomarker associated with the response to immunotherapy in prostate cancer. The heterogeneity of tumors can complicate the prediction of TMB, making reliable detection essential for effective treatment planning. Recent advancements in deep learning (DL) have facilitated the analysis of histopathologi [...]