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Big data and transformative bioinformatics in genomic diagnostics and beyond.
Parkinsonism Relat. Disord.:107311 (2025)
The current era of high-throughput analysis-driven research offers invaluable insights into disease etiologies, accurate diagnostics, pathogenesis, and personalized therapy. In the field of movement disorders, investigators are facing an increasing growth in the volume of produced patient-derived datasets, providing substantial opportunities for precision medicine approaches based on extensive information accessibility and advanced annotation practices. Integrating data from multiple sources, including phenomics, genomics, and multi-omics, is crucial for comprehensively understanding different types of movement disorders. Here, we explore formats and analytics of big data generated for patients with movement disorders, including strategies to meaningfully share the data for optimized patient benefit. We review computational methods that are essential to accelerate the process of evaluating the increasing amounts of specialized data collected. Based on concrete examples, we highlight how bioinformatic approaches facilitate the translation of multidimensional biological information into clinically relevant knowledge. Moreover, we outline the feasibility of computer-aided therapeutic target evaluation, and we discuss the importance of expanding the focus of big data research to understudied phenotypes such as dystonia.
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Publication type
Article: Journal article
Document type
Review
Keywords
Bioinformatics ; Dystonia ; Genomics ; Multi-omics ; Phenomics ; Big Data
ISSN (print) / ISBN
1353-8020
e-ISSN
1873-5126
Journal
Parkinsonism & Related Disorders
Quellenangaben
Article Number: 107311
Publisher
Elsevier
Non-patent literature
Publications
Reviewing status
Peer reviewed
Institute(s)
Institute of Neurogenomics (ING)