Editorial [Hot Topic: Clinics, Epidemiology and Genetics of Retinitis Pigmentosa (Guest Editor: Francesco Parmeggiani)]

The thematic issue on "Advanced AI Techniques in Big Genomic Data Analysis" aims to explore the cutting-edge methodologies and applications of artificial intelligence (AI) in the realm of genomic research, where vast amounts of data pose both challenges and opportunities. This issue will cover a broad spectrum of AI-driven strategies, ...read more

This special issue aims to explore the cutting-edge intersection of genomics and oncology, with a strong emphasis on original data and experimental validation. While maintaining the focus on how machine learning and advanced data analysis techniques are revolutionizing our understanding and treatment of cancer, this issue will prioritize contributions that ...read more

Recent advancements in AI and omics methodologies have revolutionized the landscape of biomedical research, enabling us to extract valuable information from vast amounts of complex data. By combining AI algorithms with omics technologies such as genomics, proteomics, metabolomics, and transcriptomics, researchers can obtain a more comprehensive and multi-dimensional analysis of ...read more

Integrating machine learning (ML) with genome science is driving transformative advancements in fields such as genomics, personalized medicine, and drug discovery. Genomic data is vast and complex, making traditional analysis methods inadequate for uncovering deep insights. Machine learning, particularly deep learning models like convolutional neural networks (CNNs) and recurrent neural ...read more