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?
Bioinformatics
Machine learning
Oncology
Pharmacokinetics
Systems biology
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.