inst/CancerGram/readme.md

In CancerGram: Prediction of Anticancer Peptides

CancerGram identifies anticancer peptides using random forests and n-gram encoding.

Restrictions: Be patient - calculations can take up to few minutes. Up to 50 sequences may be analyzed at the same time using web server. If you need larger query, please use the CancerGram package for R. * Do not use sequences shorter than 5 amino acids, and remember that CancerGram was trained on sequences up to 50 amino acids in length.

Authors: Michal Burdukiewicz, Filip Pietluch, Katarzyna Sidorczuk

Citation: Please use: Burdukiewicz, M., Sidorczuk, K., Rafacz, D., Pietluch, F., Bąkała, M., Słowik, J., and Gagat, P. (2020). CancerGram: An Effective Classifier for Differentiating Anticancer from Antimicrobial Peptides. Pharmaceutics 12, 1045, https://doi.org/10.3390/pharmaceutics12111045.

CancerGram documentation built on Nov. 19, 2020, 5:06 p.m.