Big Data Analytics in Omics Science
This special issue belongs to the section "Computational Biology, Bioinformatics, and Biomedical Data Science".
Special Issue Information
Dear Colleagues,
The rapid expansion of omics technologies, including genomics, transcriptomics, proteomics, metabolomics and metagenomics, has ushered life sciences into the era of big data. High-throughput platforms continuously generate massive, heterogeneous and multidimensional datasets, demanding innovative computational approaches to transform raw data into meaningful biological knowledge. Big data analytics has become a cornerstone of modern omics research by integrating artificial intelligence, machine learning, statistical modeling, high-performance computing and cloud-based infrastructures to uncover hidden biological patterns, identify biomarkers, predict phenotypes and support precision medicine, agriculture and environmental sciences. Despite remarkable advances, significant challenges remain in data integration, scalability, reproducibility, interoperability, visualization and the implementation of FAIR data principles. This Special Issue welcomes original research articles, datasets, software and methodological contributions addressing novel analytical frameworks, multi-omics integration, explainable AI, distributed computing, data management, visualization techniques and reproducible workflows. Contributions presenting benchmark datasets, open-source tools and real-world applications that advance biological discovery and promote data-driven innovation across omics sciences are particularly encouraged.
Dr. Adonney Allan De Oliveira Veras
Guest Editor
Manuscript Submission Information
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Keywords
- big data analytics
- multi-omics integration
- artificial intelligence
- bioinformatics
- high-performance computing
- FAIR data principles
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Published Papers
Data - ISSN 2306-5729