The web platform supports at
most 500 DNA fragments for the SNPP and 700-bp input for the MPP due to high computational complexities.
If your input size is larger than the described input sizes, you can utilize the standalone version of
ResNuc. For this purpose, please ensure that you have all the requirements listed as follows:
Python version 3.x programming language
Tensorflow machine learning library
Keras machine learning library
Python programming language
can be downloaded from python.org. It is suggested that the
above-mentioned
software packages be installed in a virtual environment which helps properly manage the files and
outputs in terms of reducing error and enhancing security. To this end, the following commands should be
considered:
If you are installing a virtual environment, it should be activated before running ResNuc (using the
source command). After installing the programming language, the TensorFlow and Keras machine learning
libraries can be installed and tested using the following commands:
pip3 install tensorflow
pip3 install keras
pip3 show keras
ResNuc is downloadable by clicking on this link and easily can
be executed
using two bellow commands for SNPP and MPP, respectively:
When confronting a technical issue, please feel free to contact us. We will gladly help you.
About Panchenko's lab
We study the associations between key components in the epigenome to understand how its perturbation can lead to cancer.
Our team works to identify factors contributing to cancer mutation occurrence in DNA, to discover molecular mechanisms of how mutations and covalent modifications
affect nucleosomes and chromatin, their interactions, stability and dynamics.