Abstract
In recent years, the genomic sequence of numerous plant species including the main crop species has been determined. Computational tools have been developed to deal with the issue of which plant has been sequenced and where is the sequence hosted. In this mini-review, the databases for genome projects, the databases created to host species/clade projects and the databases developed to perform plant comparative genomics are revised. Because of their importance in modern research, an in-depth analysis of the plant comparative genomics databases has been performed. This comparative analysis is focused in the common and specific computational tools developed to achieve the particular objectives of each database. Besides, emerging high-performance bioinformatics tools specific for plant research are commented. What kind of computational approaches should be implemented in next years to efficiently analyze plant genomes is discussed.
Keywords: Comparative genomics, Computational tools, Genome databases, Genome projects, Plants.
Graphical Abstract
Call for Papers in Thematic Issues
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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
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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
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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
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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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