Research Reports on Bioinformatics from Carnegie Mellon University Provide New Insights (Integrating patients in time series clinical transcriptomics data).

A recent study from Carnegie Mellon University explores the challenges of analyzing time series transcriptomics data from clinical trials. The researchers developed a new method that utilizes multi-commodity flow algorithms to infer trajectories in large-scale clinical studies. This method improves upon previous approaches by accounting for varying response rates and subgroups within a patient cohort, and it has demonstrated improved performance and the ability to identify novel disease subtypes. The source code and data for this study are available on GitHub. [Extracted from the article]

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