Cross-Study Machine Learning Techniques: Reproducibility and Differences Across Studies

Biostatistics and computational biology are increasingly facing the urgent challenge of efficiently dealing with a large amount of experimental data. In particular, high-throughput assays are transforming the study of biology, as they generate a rich, complex, and diverse collection of high-dimensional data sets. Through compelling statistical analysis, these large data sets lead to discoveries, advances and knowledge that were never accessible before, via compelling statistical analysis. Building such systematic knowledge is a cumulative process which requires analyses that integrate multiple sources, studies, and technologies.

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