2023
DOI: 10.21203/rs.3.rs-2811853/v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

Proposing New Potential Candidates to Inhibit EGFR via Machine Learning Algorithm

Abstract: One of the main issues in solid tumours is progressive mutation in epidermal growth factor receptors (EGFR) gene, which activates signalling pathways that create new blood vessels. In this study, it was attempted to find new a therapeutic candidate to inhibit EGFR. One of the cost-effective alternative methods to find new inhibitors has been the repositioning approach of existing drugs. The critical point of computational drug repositioning method is saving time and cost to remove the pre-clinical step and acc… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
references
References 36 publications
0
0
0
Order By: Relevance