<img src="Cancergram2.png" alt="logo" style="width: 200px;"/>

**CancerGram** identifies anticancer peptides using [random forests](https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm) and [n-gram encoding](http://github.com/michbur/biogram).   

**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](https://CRAN.R-project.org/package=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.
