Histology is the cornerstone of clinical pathology and an essential tool for many areas of medicine. Nevertheless, conventional histological methods, which rely on fixation, embedding, sectioning, and staining, distort cellular architecture, extract ...
Prochlorococcus is a cyanobacterial genus that exhibits photosynthetic capacity and remarkable genetic diversity. We analyze how Prochlorococcus genomics relate to high vs. low light environment adaptations, applying traditional comparative genomics ...
The diagnosis of neurological disorders requires comprehensive frameworks that incorporate multimodal neuroimaging data while ensuring clinical interpretability. Recent neuroimaging research is focusing on the integration of brain structure and funct...
Advances in functional magnetic resonance imaging (fMRI) have led to the ability to study the brain across many contexts. However, the large number of features generated by functional connectivity approaches may overfit the data. These problems can b...
Exploring the dynamics of a complex system, such as the human brain, poses significant challenges due to inherent uncertainties and limited data. In this study, we enhance the capabilities of noisy linear recurrent neural networks (lRNNs) within the ...
The tumor microenvironment (TME) significantly impacts cancer progression and overall patient survival. However, the complexity of tumor cell-TME interactions in gastric cancer (GC) and their underlying molecular basis remain to be systematically elu...
The flexible deployment of cognitive control is essential for adaptive functioning in dynamic environments given limited cognitive resources. That flexibility depends on rapid detection and resolution of control- prediction errors (CPEs) when current...
Machine learning (ML) models with stochastic and non-deterministic characteristics are increasingly used for genomic prediction in plant breeding, but evaluation often neglects important aspects like prediction stability and ranking performance. This...
High-throughput chromosome conformation capture sequencing (Hi-C) is a key technology for studying the three-dimensional (3D) structure of genomes and chromatin folding. Hi-C data reveals underlying patterns of genome organization, such as topologica...
High-fidelity scoring of RNA 3D structures remains a major challenge in RNA structure prediction and conformational sampling. While single-model methods for scoring RNA structures can capture individual structural features, they fail to capture the b...
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