This repository contains the source code for the SmartCut algorithm. The SmartCut algorithm is designed to split input DNA sequences into oligonucleotides using a deep learning-based model. These strands are used for polymerase cycling assembly.
The SmartCut algorithm is based on TensorFlow version 2.6.0. All other necessary packages are listed in requirements.txt.
The algorithm has been tested and confirmed to work on the following platforms:
- Windows 10/11
- Ubuntu 20.04
- CentOS 7.5
Run the design_genome.py script as an example. This script applies the SmartCut algorithm to split the sequences of chromosomes and genomes.
The sequencing_results folder contains sequencing files for the DNA sequences from data_for_Table1.xlsx that were designed and synthesized.
design_genome.py: Script to run the SmartCut algorithm for chromosome and genome sequence splitting.sequencing_results: Folder containing the sequencing results of designed DNA sequencesdata_for_Table1.xlsx.requirements.txt: List of required Python packages.