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Data-Driven Modelling of Substituted Pyrimidine and Uracil-Based Derivatives Validated with Newly Synthesized and Antiproliferative Evaluated Compounds

Uko Maran

The pyrimidine heterocycle plays an important role in anticancer research. In particular, the pyrimidine derivative families of uracil show promise as structural scaffolds relevant to cervical cancer. This group of chemicals lacks data-driven machine learning quantitative structure-activity relation...

Interpretable machine learning for the identification of estrogen receptor agonists, antagonists, and binders - a tool for identifying risks from chemicals

Uko Maran

An abnormal hormonal activity or exposure to endocrine-disrupting chemicals (EDCs) can cause endocrine system malfunction. Among the many interactions EDCs can affect is the disruption of estrogen signaling, which can lead to adverse health effects such as cancer, osteoporosis, neurodegenerative dis...

Pesticide effect on earthworm lethality via interpretable machine learning a tool for identifying risk to environment caused by chemicals

Uko Maran

Earthworms are among the most important animals (invertebrates) for soil health. Many chemical substances released into nature for agricultural development, such as pesticides, may have unwanted effects on those organisms. However, it is essential to understand the extent of the impact of chemicals...