SpectraFP 1.2.5

A package to perform fingerprints from spectroscopy datas.

Publication

This is the official repository for the article entitled: "SpectraFP: a new spectra-based descriptor to aid in cheminformatics, molecular characterization and search algorithm applications" published in the journal Physical Chemistry Chemical Physics (PCCP).

DOI: https://doi.org/10.1039/D3CP00734K

How to cite

Bibtex:

@article{dias2023spectrafp,
  title={SpectraFP: a new spectra-based descriptor to aid in cheminformatics, molecular characterization and search algorithm applications},
  author={Dias-Silva, Jefferson R and Oliveira, Vitor M and Sanches-Neto, Fl{\'a}vio O and Wilhelms, Renan Z and J{\'u}nior, Luiz HK Queiroz},
  journal={Physical Chemistry Chemical Physics},
  volume={25},
  number={27},
  pages={18038--18047},
  year={2023},
  publisher={Royal Society of Chemistry}
}

Text:

Dias-Silva, Jefferson R., et al. "SpectraFP: a new spectra-based descriptor to aid in cheminformatics, molecular characterization and search algorithm applications." Physical Chemistry Chemical Physics 25.27 (2023): 18038-18047.

Dias-Silva, J. R., Oliveira, V. M., Sanches-Neto, F. O., Wilhelms, R. Z., & Júnior, L. H. Q. (2023). SpectraFP: a new spectra-based descriptor to aid in cheminformatics, molecular characterization and search algorithm applications. Physical Chemistry Chemical Physics, 25(27), 18038-18047.

DIAS-SILVA, Jefferson R., et al. SpectraFP: a new spectra-based descriptor to aid in cheminformatics, molecular characterization and search algorithm applications. Physical Chemistry Chemical Physics, 2023, 25.27: 18038-18047.

SpectraFP

SpectraFP is a package to perform fingerprints from spectroscopy datas. The goal is to transform a list of spectroscopy signals - such as nmr and infrared - into a binary vector of zeros and ones. One means that there is a sign and zero absence.

Install

Via pypi

$ pip install spectrafp

Via github

$ git clone https://github.com/jeffrichardchemistry/SpectraFP
$ cd SpectraFP
$ python3 setup.py install

Tutorials

Tutorials on how to use this package as well as loading the databases are available in the jupyter-notebook file in example/how_to_use.ipynb and Reading pickle data.ipynbrespectively.