Research Paper on After applying the Random Forest algorithm to the QSAR model after performing cluster analysis, machine learning is used to assess the cytotoxicity of mixtures of nano-TiO2 and heavy metals.

Description

Title: After applying the Random Forest algorithm to the QSAR model after performing cluster analysis, machine learning is used to assess the cytotoxicity of mixtures of nano-TiO2 and heavy metals.

Abstract: The effects of nanomaterials on the environment and living things have come under scrutiny with the development and use of these materials. Nano-titanium dioxide (nano-TiO2) is a typical nanomaterial that has the ability to bind to heavy metals in the environment. It is frequently used to forecast the cytotoxicity of a single substance using the quantitative structure-activity relationship (QSAR). On the toxicity of interactions between nanomaterials and other substances, there is, however, little research. In this study, human renal cortex proximal tubule epithelial (HK-2) cells were exposed to nano-TiO2 and a mixture of eight heavy metals. CCK-8 was used to measure absorbance values, and cell viability was calculated. Multiple QSAR models are created for data sets using PLS and two ensemble learning algorithms, increasing the test set R2 from 0.38 to 0.78 and 0.85 and reducing the RMSE from 0.18 to 0.12 and 0.10. Following the selection of the superior random forest algorithm, the model is further optimized using the K-means clustering algorithm, which raises the test set R2 to 0.95 and lowers the RMSE to 0.08 and 0.06. Random forest can be used to accurately predict the toxicity of a mixture of heavy metals and nano-metal oxides. The cluster analysis can significantly increase the model’s stability and predictability and offer a fresh concept for cytotoxicity model prediction in the future.

Keywords: QSAR; Ada Boost; RF; cluster analysis; mixture; cytotoxicity; quantum mechanics

Paper Quality: SCOPUS / Web of Science Level Research Paper

Subject: Chemistry

Writer Experience: 20+ Years

Plagiarism Report: Turnitin Plagiarism Report will be less than 10%

Restriction: Only one author may purchase a single paper. The paper will then indicate that it is out of stock.

What will I get after the purchase?

A turnitin plagiarism report of less than 10% in a pdf file and a full research paper in a word document.

In case you have any questions related to this research paper, please feel free to call/ WhatsApp on +919726999915