Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks

• Published in: Scientific reports Vol. 10; no. 1; p. 8515
• Main Authors: López-Cortés, Andrés, Cabrera-Andrade, Alejandro, Vázquez-Naya, José M., Pazos, Alejandro, Gonzáles-Díaz, Humberto, Paz-y-Miño, César, Guerrero, Santiago, Pérez-Castillo, Yunierkis, Tejera, Eduardo, Munteanu, Cristian R.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.05.2020; Nature Publishing Group
• Subjects: 119/118; 631/67/1347; 692/4028/67/1347; Amino acid sequence; Biomarkers, Tumor - genetics; Breast cancer; Breast Neoplasms - metabolism; Breast Neoplasms - secondary; Breast Neoplasms - therapy; Cancer immunotherapy; Deregulation; Drug development; Female; Gene Expression Profiling; Gene Expression Regulation, Neoplastic; Genomics; Humanities and Social Sciences; Humans; Immunotherapy; Immunotherapy - methods; Learning algorithms; Machine Learning; Metastases; Metastasis; multidisciplinary; Neoplasm Metastasis; Neural networks; Neural Networks, Computer; Predictions; Proteins; Ribonucleic acid; RNA; RNA - metabolism; RNA-binding protein; Science; Science (multidisciplinary); Signal transduction; Therapeutic applications

Breast cancer (BC) is a heterogeneous disease where genomic alterations, protein expression deregulation, signaling pathway alterations, hormone disruption, ethnicity and environmental determinants are involved. Due to the complexity of BC, the prediction of proteins involved in this disease is a tr...