López-Cortés2020 - Prediction of Breast Cancer (BC) proteins involved in cancer immunotherapy using molecular descriptors and Multi Layer Perceptron (MLP) neural network

ABSTRACT: This study introduces a predictive classifier for breast cancer-related proteins, utilising a combination of protein sequence descriptors and machine learning techniques. The best-performing classifier is a Multi Layer Perceptron (artificial neural network) with 300 features, achieving an average Area Under the Receiver Operating Characteristics (AUROC) score of 0.984 through 3-fold cross-validation. Notably, the model identified top-ranked cancer immunotherapy proteins associated with breast cancer that should be studied for further biomarker discovery and therapeutic targeting. Please note that in this model, the output '0' means BC non-related protein and '1' means BC related protein. The original GitHub repository can be accessed at https://github.com/muntisa/neural-networks-for-breast-cancer-proteins

SUBMITTER: Divyang Deep Tiwari  

PROVIDER: BIOMD0000001076 | BioModels | 2023-10-09

REPOSITORIES: BioModels