Current Genomics
Title:Editorial [Hot Topic: Genetics Dissection of Complex Traits in the Genomic Era (Guest Editor: Bernardo Ordas)]
Volume: 13 Issue: 3
Author(s): Bernardo Ordas
Affiliation:
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Ordas Bernardo, Editorial [Hot Topic: Genetics Dissection of Complex Traits in the Genomic Era (Guest Editor: Bernardo Ordas)], Current Genomics 2012; 13 (3) . https://dx.doi.org/10.2174/138920212800543075
DOI https://dx.doi.org/10.2174/138920212800543075 |
Print ISSN 1389-2029 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5488 |
Call for Papers in Thematic Issues
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, ...read more
Current Genomics in Cardiovascular Research
Cardiovascular diseases are the main cause of death in the world, in recent years we have had important advances in the interaction between cardiovascular disease and genomics. In this Research Topic, we intend for researchers to present their results with a focus on basic, translational and clinical investigations associated with ...read 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 ...read 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 ...read more
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