AI in Genomic Analysis

In recent years, the application of artificial intelligence (AI) has revolutionized the fields of genomics and precision medicine, among others. This convergence of AI and genomics is enabling unprecedented insights into complex biological systems and driving advancements in personalized healthcare solutions. Genomic data, by nature, is extensive and multifaceted, posing substantial challenges in data analysis, interpretation, and integration. Traditional approaches often struggle with the high-dimensionality and noise inherent in genomic datasets. AI, with its ability to learn patterns and make predictions from large datasets, provides a transformative approach to managing and interpreting genomic information.

AI methodologies, particularly machine learning and deep learning, have demonstrated significant potential in various genomic applications. These include identifying genetic variants associated with diseases, predicting disease risks, and uncovering therapeutic targets. The integration of AI-tools in genomics has improved the speed and accuracy of genetic sequence analysis, enhanced variant interpretation, and facilitated the understanding of non-coding regions of DNA. Furthermore, AI-based programs are advancing the exploration of gene expression patterns and the elucidation of complex polygenic traits, thereby offering new avenues for research and discovery in genomics.

This research topic aims to explore the innovative applications and developments of AI in genomic analysis. It seeks to highlight cutting-edge research that leverages AI techniques to advance our understanding of genomics, improve disease diagnosis, and inform therapeutic strategies.

We invite submissions that present original research, reviews, methodologies, technology and code articles and perspectives within the field of AI-driven genomic analysis. Submissions can focus on the development and application of AI techniques to address challenges and propel advancements in genomics. We welcome contributions that explore but are not limited to:

1. AI-Driven Variant Calling and Annotation: Papers examining enhanced methods for detecting and interpreting genetic variants using AI techniques.
2. Predictive AI-Modeling in Genomics: Research focusing on AI models that predict disease risk, progression, or response to treatment based on genomic data.
3. Gene expression and regulation and AI: Studies exploring AI applications in understanding gene expression, regulation, and the functional impact of genetic variations.
4. Functional prediction of genes. The function of many genes, all the way from viruses to humans, remains unknown. Papers describing research that applies AI to this problem are welcome.
5. AI in Epigenomics: Investigations into AI tools used for analyzing epigenetic modifications and their implications for health and disease.
6. AI-Assisted Genomic Analysis for Medicine: Articles assessing the role of AI in tailoring medical treatments based on individual genomic profiles.
7. AI in Microbiomics. Research that applies AI in the understanding of microbiomes.
8. Ethical and Social Implications of AI in Genomics: Discussions on the ethical considerations of AI applications in genomics, including data privacy, bias, and the societal impact of genomic technologies.

Through this research topic, we aim to foster a comprehensive discourse on leveraging AI for significant advancements in genomics, inviting pioneering ideas and discussions that pave the way for future developments in the field.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: Artificial Intelligence, Genomics, Precision Medicine, Genomic Analysis, Variant, Functional Genomics, Ethics

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.