Current Genomics
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Editor-in-Chief:
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Fabio Coppede Department of Translational Research and of New Surgical and Medical Technologies
University of Pisa
Pisa
Italy
ISSN: 1389-2029 (Print)
eISSN: 1875-5488 (Online)
Special Issues With Active Call for Papers
Exploration of Tumor Biomarkers and Precision Diagnosis and Treatment through Multi-Omics Integration
Precision medicine offers new hope for tumor diagnosis and treatment by creating personalized plans based on individual patient characteristics like genes, proteins, and metabolites, improving outcomes and reducing side effects. The focus is now on discovering new targets and biomarkers to advance drug development and personalized targeted therapy. Despite breakthroughs, cancer's heterogeneity necessitates broader research on drugs and biomarkers. This topic highlights cutting-edge research in multi-omics integration for tumor biomarkers and precision treatment, gathering experts... see more
Integrating Machine Learning and Multiple Omics to Uncover Complex Immunity in Human Diseases
The intricate interplay between immune system dysregulation and human diseases remains incompletely mapped and deciphered, posing a great barrier to effective therapies. Recent advances in high-throughput omics technologies (genomics, transcriptomics, epigenomics, etc.) and spatial techniques generate vast multi-dimensional data, paving the way for deepening data mining. Sophisticated machine learning (ML) and artificial intelligence (AI) methods offer unprecedented power to integrate these complex layers, predict disease trajectories, and pinpoint novel therapeutic targets within the immune landscape.... see more
AI-Driven Genomics and Multi-Omics Approaches for Drug Discovery and Precision Medicine
The rapid advancements in artificial intelligence (AI) have opened new avenues in genomics and multi-omics research, providing transformative insights into disease mechanisms, biomarker discovery, and therapeutic strategies. This thematic issue explores the intersection of AI with genomics, transcriptomics, proteomics, metabolomics, and epigenomics, focusing on how computational intelligence can facilitate data integration and interpretation across diverse biological datasets. Key focus areas include AI-driven models for genomic variant analysis, single-cell and spatial transcriptomics, epigenetic modifications, and systems... see more
Advances in Genomics and Precision Medicine for Cardiovascular Diseases
Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality globally, representing a significant challenge to public health systems. Recent advancements in genomics and precision medicine offer unprecedented opportunities to transform the prevention, diagnosis, and treatment of CVDs. This special issue of Current Genomics explores the latest developments in these fields, highlighting the integration of genomic technologies with clinical practice. The application of next-generation sequencing, genome-wide association studies, and transcriptomic profiling has led to... see more
Emerging Molecular Mechanisms in Rare Genetic Skeletal Disorders: Linking Genomic Mutations to Clinical Outcomes.
Rare genetic skeletal disorders encompass a diverse group of conditions that impact bone and cartilage development, often due to pathogenic mutations in critical developmental genes. This thematic issue aims to explore the intricate molecular mechanisms underlying these disorders, providing insights into how specific genomic mutations translate into clinical phenotypes. Recent advances in genomic sequencing and bioinformatics have facilitated the identification of novel mutations and pathways associated with skeletal dysplasia, osteogenesis imperfecta, and other rare bone... see more
Integrating Artificial Intelligence and Omics Approaches in Complex Diseases
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 biological systems, ultimately leading to a better understanding of disease mechanisms. Complex diseases, characterized by their heterogeneous nature, pose unique challenges to researchers and clinicians... see more
Genomic Insights into Oncology: Harnessing Machine Learning for Breakthroughs in Cancer Genomics.
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 go beyond mere data-mining. We seek to include comprehensive review articles that synthesize recent advancements and research papers that present novel data, demonstrating clear experimental... see more
Integrating Machine Learning with Genome Science: Pioneering Developments and Future Directions
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 networks (RNNs), has become essential for efficiently analyzing genetic sequences, identifying mutations, and predicting the links between genotype and phenotype. In personalized medicine, ML helps... see more
Advanced AI Techniques in Big Genomic Data Analysis
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, including machine learning and deep learning models, tailored for extracting, analyzing, and interpreting complex patterns within large-scale genomic datasets. Contributions to this issue will highlight... see more