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Reference baseline for high-performance cheminformatics fingerprint search benchmarking

Project description

This version of chemfp includes command-lines tools to generate
cheminformatics fingerprints and search those fingerprints by
Tanimoto similarity, as well as a Python library which you can use
to build new tools.

It is the no-cost/open source chemfp release track. It only supports
Python 2.7. It is being maintained only to provide a good reference
baseline for benchmarking other similarity search tools.

The commercial track, currently chemfp 3.4, includes faster
performance, many new features, and support for Python 3.

Chemfp is designed for the dense, 100-10,000 bit fingerprints which
occur in small-molecule/pharmaceutical chemisty. The Tanimoto search
algorithms are implemented in C and assembly for performance, and
support both threshold and k-nearest searches using the BitBound
algorithm of Swamidass and Baldi.

Fingerprint generation can be done either by extracting existing
fingerprint data from an SD file or by using an existing chemistry
toolkit. chemfp supports the Python libraries from Open Babel,
OpenEye, and RDKit toolkits. Be aware that those vendors no longer
support Python 2.7.

The main web site is https://chemfp.com/ .

Extensive documentation is at https://chemfp.readthedocs.io/ .

To cite chemfp use:
Dalke, Andrew. The chemfp project. J. Cheminformatics 11, 76
(2019). https://doi.org/10.1186/s13321-019-0398-8
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-019-0398-8


Project details


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