Spritan/ParkinsonDisease_ProteinClassifier
A machine learning pipeline for classifying protein sequences associated with Parkinson's disease using various sequence features and multiple classification models. The project achieves 80.3% accuracy using LSTM architecture with comprehensive sequence feature analysis.
This project helps medical researchers and biologists classify protein sequences to identify those associated with Parkinson's disease. You input FASTA files containing various protein sequences, and it outputs a classification indicating whether each protein is linked to Parkinson's. This tool is for scientists working on disease diagnostics or drug discovery related to neurodegenerative disorders.
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Use this if you need to quickly identify potential Parkinson's disease-associated proteins from a set of protein sequences to accelerate research or diagnostic development.
Not ideal if you require 100% diagnostic certainty from a single model or need to classify proteins for diseases other than Parkinson's.
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Language
Python
License
MIT
Category
Last pushed
Nov 18, 2024
Commits (30d)
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