How can advancements in bioinformatics tools and multi-omics integration (genomics, transcriptomics, and proteomics) improve the early diagnosis of cancer in 2024?
How can bioinformatics tools optimize the integration of multi-omics data to identify highly specific and sensitive biomarkers for early cancer diagnosis?
· What role does artificial intelligence play in analyzing complex biological datasets, and how can its predictions be validated for clinical use?
· What challenges exist in the standardization of bioinformatics pipelines for regulatory approval and widespread clinical adoption?
· How can researchers address issues such as data heterogeneity, small sample sizes, and the need for longitudinal studies to improve biomarker reliability?
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Ragothaman Yennamalli
AI can accelerate the process, but currently there is lot of noise in the data that may give lots of false positive to a trained AI.