Professor Broom's research interests include the analysis of high-throughput bioinformatics data, scientific visualization, machine learning, and reproducible analysis. FjORD, an enterprise information system for managing a large assortment of reproducible data analyses; GeneClust, an implementation of the "Gene Shaving" method for finding gene clusters; Next-Generation Clustered Heat Maps, large-scale interactive clustered heat maps suitable for the interactive exploration of large bioinformatics (and other) data sets; DyCE, a dynamic computational environment; MetaBatch, an Adaptation of the MBatch environment for detecting, evaluating, and ameliorating batch effects in Metabolomic data.
Publications/Creative Works
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