Computational Methods for the Analysis and Prediction of EGFR-mutated Lung Cancer Drug Resistance: Recent Advances in Drug Design, Challenges and Future Prospects-Reference-Cited by-同舟云学术

Computational Methods for the Analysis and Prediction of EGFR-mutated Lung Cancer Drug Resistance: Recent Advances in Drug Design, Challenges and Future Prospects

Published:2022 Issue: Volume: Page:1-1
ISSN:1545-5963
Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
language:
Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Qureshi Rizwan,Zou Bin,Alam Tanvir,Wu Jia,Lee Victor,Yan Hong

Funder

Hong Kong Research Grants Council

City University of Hong Kong

Innovation and Technology Commission Hong Kong InnoHK Project CIMDA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Link

http://xplorestaging.ieee.org/ielx7/8857/4359833/09676451.pdf?arnumber=9676451

Reference169 articles.

1. Prediction of sensitivity to gefitinib/erlotinib for EGFR mutations in NSCLC based on structural interaction fingerprints and multilinear principal component analysis

2. Hydrogen bond analysis of the EGFR-ErbB3 heterodimer related to non-small cell lung cancer and drug resistance

3. Structural investigations of T854A mutation in EGFR and identification of novel inhibitors using structure activity relationships

4. The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP

5. HOMOLOGY MODELING AND MOLECULAR DYNAMICS STUDIES OF EC1 DOMAIN OF VE-CADHERIN TO ELUCIDATE DOCKING INTERACTION WITH CADHERIN-DERIVED PEPTIDE

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