Deep Learning Model (RNN, LSTM, GRU, RBM, DBN, AE) for Saccharomyces Cerevisiae
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data
models
.gitignore
AutoEncoderModel.py
Confirming DNA Replication Origins of Saccharomyces Cerevisiae A Deep Learning Approach.pdf
LICENSE
PreprocessGenerative.py
README.md
RestrictedBoltzmannMachineModel.py
au.py
capture.log
dbnModel_2Layers.py
dbnModel_4Layers.py
model.py
rbm.py
sample.py
sample.sh
train.py
train.sh
training.log
utils.py

README.md

Deep Learning Model for Saccharomyces Cerevisiae

Saccharomyces Cerevisiae is a species of yeast. It has been instrumental to winemaking, baking, and brewing since ancient times. The origin of replication in cerevisiae genome has been studied for years and more origins are being dicovered in research labs all over the world, by carrying out biological experiments.

In this project, we are building a deep learning model that tries to find hidden relationships in the whole genomic sequence of cerevisiae (divided into 16 chromosomes). Training the model on the confirmed replication origin sites, we are expecting that the model is going to confirm or disconfirm other disocvered replication origins that are marked "likely" or "dubious".

References to datasets

Whole Genome Sequence: Saccharomyces Genome Database

Replication Origins: OriDB

Current Progress

Check project page

Contributors

Abdelrahman Hosny, Anthony Parziale