Tensorflow 2.0 implementation of classification of the genetic code sequence. Genetic code has form of Nucleobases sequence (A C T G). We use GRU cells (Gated Recurrent Units) to classyfie given sequence to one of five classes.
The obtained results are surprisingly good, thanks to usage of GRU cells it was possible to achive about 100% accuracy on both validation and training set.
To run it You need jupyter notebook installed or You can run it using google colab The main file is Classifying-Nucleic-Acid-Sequence.ipynb
-tensorflow 2.0
-numpy
-tqdm
-matplotlib
Data used in this repo was taken from FU Berin Deep Learnig Course (Prof. Frank Noé Sommer Semeter 2019)
This project is licensed under the MIT License - see the LICENSE.md file for details