Pangenomes exhibit remarkable variability in many prokaryotic species, much of which is
maintained through the processes of horizontal gene transfer and gene loss. Repeated …

BACKGROUND Cabbage stem flea beetle (CSFB; Psylliodes chrysocephala L.)
management in oilseed rape (Brassica napus L.) has become an urgent issue in the …

This comprehensive review delves into the intersection of ensemble machine learning
models and interpretability techniques for biomass and waste gasification, a field crucial for …

Background Despite advancements in neonatal care, germinal matrix-intraventricular
hemorrhage impacts 20% of very preterm infants, exacerbating their neurological prognosis …

Quantitative structure-activity relationship (QSAR) modeling is a powerful tool for drug
discovery, yet the lack of interpretability of commonly used QSAR models hinders their …

Protection of groundwater resources is essential to ensure quality and sustainable use.
However, predicting vulnerability to anthropogenic pollution can be difficult where data are …

Background and Objectives Epilepsy surgery is often delayed. We previously developed
machine learning (ML) models to identify candidates for resective epilepsy surgery earlier in …

Sequences are prevalent in myriad real-world scenarios, making it imperative to discern the
mechanisms behind symbol generation and, subsequently, to decode complex system …

Forest plantations are increasingly recognized for their role in providing ecosystem services
in agroforestry systems. Understanding the habitat preferences of potentially beneficial birds …

Background Intramedullary spinal cord tumors are challenging to resect, and their
postoperative neurological outcomes are often difficult to predict, with few studies assessing …