Featured Project
Analyzing Noncoding DNA Mutation For Melanoma Cancer with CNN AI Models Supervised Training
Description
This project aims to develop a predictive model which intakes raw DNA sequence data to estimate the likelihood of a mutation driving melanoma cancer along noncoding sequences of DNA. The model architecture of Convolutional Neural Network (CNN) will be trained under the supervised training method to utilize the robust datasets of noncoding mutated variants seen as melanoma-linked or benign. The impact of such a model could further research for early risk assessment of melanoma cancer.
Technical Stack
- Model: Convolutional Neural Network (CNN)
- Frameworks/Libraries: Python, TensorFlow/PyTorch
- Tools: R statistical analysis and visualization
- Data Sources include Publicly available genomic databases for supervised learning