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ChemTreeMap: an interactive map of biochemical similarity in molecular datasets

Lu, Jing, Carlson, Heather A.
Bioinformatics 2016 v.32 no.23 pp. 3584-3592
algorithms, bioactive properties, bioinformatics, color, data collection, leaves, structure-activity relationships
Motivation: What if you could explain complex chemistry in a simple tree and share that data online with your collaborators? Computational biology often incorporates diverse chemical data to probe a biological question, but the existing tools for chemical data are ill-suited for the very large datasets inherent to bioinformatics. Furthermore, existing visualization methods often require an expert chemist to interpret the patterns. Biologists need an interactive tool for visualizing chemical information in an intuitive, accessible way that facilitates its integration into today’s team-based biological research. Results: ChemTreeMap is an interactive, bioinformatics tool designed to explore chemical space and mine the relationships between chemical structure, molecular properties, and biological activity. ChemTreeMap synergistically combines extended connectivity fingerprints and a neighbor-joining algorithm to produce a hierarchical tree with branch lengths proportional to molecular similarity. Compound properties are shown by leaf color, size and outline to yield a user-defined visualization of the tree. Two representative analyses are included to demonstrate ChemTreeMap’s capabilities and utility: assessing dataset overlap and mining structure–activity relationships. Availability and Implementation: The examples from this paper may be accessed at Code for the server and client are available in the Supplementary Information, at the aforementioned github site, and on Docker Hub ( with the nametag ajing/chemtreemap. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.