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

**AmyloGram** predicts amyloidogenic sequences (hot spots) in eukaryotic proteins using [random forests](https://www.stat.berkeley.edu/~breiman/RandomForests/cc_home.htm) and [n-gram analysis](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 [AmyloGram](https://CRAN.R-project.org/package=AmyloGram) package for **R**.

**Authors**: [Michal Burdukiewicz](http://www.smorfland.uni.wroc.pl/), [Piotr Sobczyk](http://prac.im.pwr.wroc.pl/~sobczyk/).

**Citation**:
[Burdukiewicz, M., Sobczyk, P., Rödiger, S., Duda-Madej, A., Mackiewicz, P., and Kotulska, M. (2017). Amyloidogenic motifs revealed by n-gram analysis. Scientific Reports 7, 12961.](https://www.nature.com/articles/s41598-017-13210-9)

**Examplary input**:


