fMLC: Fast Multi-Level Clustering and Visualization of Large Molecular Datasets

D Vu, S Georgievska, S. Szoke, A. Kuzniar, V Robert

Research output: Contribution to journal/periodicalArticleScientificpeer-review


Motivation: Despite successful applications of data clustering and visualization techniques in molecular sequence identification, current technologies still do not scale to large biological datasets.

Results: We address this problem by a new multi-threaded tool, fMLC, primarily developed to cluster DNA sequences, that is supplemented with an interactive web-based visualization component, DiVE. fMLC enabled to compare, cluster and visualize 350K ITS fungal sequences at the species level. It took less than two hours to compare and cluster the dataset, which is twelve times faster than the time reported previously.

Availability: (doi: 0.5281/zenodo.926820).


Original languageEnglish
Publication statusPublished - 15 Dec 2017


  • Journal Article


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