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Prediction of Cell-Penetrating Peptides using Artificial Neural Networks
- Publication Year :
- 2010
-
Abstract
- An investigation of cell-penetrating peptides (CPPs) by using combination of Artificial Neural Networks (ANN) and Principle Component Analysis (PCA) revealed that the penetration capability (penetrating/non-penetrating) of 101 examined peptides can be predicted with accuracy of 80%-100%. The inputs of the ANN are the main characteristics classifying the penetration. These molecular characteristics (descriptors) were calculated for each peptide and they provide bio-chemical insights for the criteria of penetration. Deeper analysis of the PCA results also showed clear clusterization of the peptides according to their molecular features.
Details
- Database :
- OAIster
- Notes :
- English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1234845874
- Document Type :
- Electronic Resource
- Full Text :
- https://doi.org/10.2174.157340910791202478