Prediction of Aptamer Protein Interaction Using Random Forest Algorithm

Prediction of Aptamer Protein Interaction Using Random Forest Algorithm

Aptamers are oligonucleotides that may attach to amino acids, polypeptide, tiny compounds, allergens and living cell membrane. Therapeutics, bio sensing and diagnostics are all sectors where the aptamers may be used. In this work, we present a model based on Random Forest Algorithms to predict the i...

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Bibliographic Details
Main Authors: N. Manju, C. M. Samiha, S. P. Pavan Kumar, H. L. Gururaj, Francesco Flammini
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Aptamers
random forest algorithm (RFA)
random forest feature importance (RFFI)
XGBoost feature importance (XGBFI)
principal component analysis (PCA)
psuedo amino acid composition (PseAAC)
Online Access:https://ieeexplore.ieee.org/document/9766308/

Internet

https://ieeexplore.ieee.org/document/9766308/

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