Version 1
: Received: 5 September 2024 / Approved: 6 September 2024 / Online: 10 September 2024 (13:50:53 CEST)
How to cite:
Sinha, S. Machine Learning Discoveries of ANTXR2-X Synergy in etc-1922159 Treated Colorectal Cancer Cells. Preprints2024, 2024090817. https://doi.org/10.20944/preprints202409.0817.v1
Sinha, S. Machine Learning Discoveries of ANTXR2-X Synergy in etc-1922159 Treated Colorectal Cancer Cells. Preprints 2024, 2024090817. https://doi.org/10.20944/preprints202409.0817.v1
Sinha, S. Machine Learning Discoveries of ANTXR2-X Synergy in etc-1922159 Treated Colorectal Cancer Cells. Preprints2024, 2024090817. https://doi.org/10.20944/preprints202409.0817.v1
APA Style
Sinha, S. (2024). Machine Learning Discoveries of ANTXR2-X Synergy in etc-1922159 Treated Colorectal Cancer Cells. Preprints. https://doi.org/10.20944/preprints202409.0817.v1
Chicago/Turabian Style
Sinha, S. 2024 "Machine Learning Discoveries of ANTXR2-X Synergy in etc-1922159 Treated Colorectal Cancer Cells" Preprints. https://doi.org/10.20944/preprints202409.0817.v1
Abstract
Often, in biology, we are faced with the problem of exploring relevant unknown biological hypotheses in the form of myriads of combinations of factors/genes/proteins that might be affecting the pathway under certain conditions. In colorectal cancer (CRC) cells treated with ETC-1922159, many genes were found up and down regu- lated, individually. A recently developed search engine ranked combinations of AN- TXR cell adhesion molecule 2 (ANTXR2)-X (X, a particular gene/protein) at 2nd order level after drug administration. These rankings reveal which ANTXR2-X combinations might be working synergistically in CRC. If found true, oncologists can further test the combination of interest in wet lab and determine the mechanism of functioning be- tween the ANTXR2 and X. In this research work, we cover combinations of ANTXR2 with Collagen (COL), Integrin (ITG), Matrix metalloproteinases (MMP), WNT, TNF and Interleukin (IL) .
Keywords
ANTXR2,PorcupineinhibitorETC-1922159,Sensitivityanalysis, Colorectal cancer
Subject
Computer Science and Mathematics, Mathematical and Computational Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
