The concept of embodied sensorimotor decision-making proposes that processes implicated in evaluating sensory inputs and selecting appropriate motor actions unfold partly in cortical regions traditionally associated with movement planning and executi...
Visual working memory is essential for navigating through and interacting with complex real-world environments. It is therefore important to understand how natural visual inputs - characterized by complex contours, continuously varying feature gradie...
Motivation: One of the challenges encountered when merging heterogeneous observational clinical datasets is the recoding of categorical target variables that may have been measured differently across data sources. Standard machine learning-based appr...
Neurophysiologists have discovered many mechanisms underlying the production of animal behaviors in specific species; these involve a collection of neuromuscular systems, neuronal membrane and neural network properties, as well as the hormones and ne...
Identifying common function-determining structural motifs among proteins with different folds is a foundational task in computational biology with no go-to solution. Indeed, standard alignment tools like TM-align are ill-suited for matching small, se...
Accurate pose estimation underpins quantitative analysis of behavior, yet many deep learning-based tracking tools remain optimized for offline workflows that rely on fragmented software pipelines, workstation-grade GPUs, or external middleware to ena...
Multidrug-resistant hypervirulent Klebsiella pneumoniae (MDR-hvKP) poses a severe global health threat. Phage therapy is a promising alternative, but requires precise matching of phage to the bacterial strain. Here, we present a proof-of-concept meth...
Multiple sequence alignment (MSA) data underlies current principles in protein folding and protein-protein interaction prediction, from which large language models (LLMs) in tandem with protein datasets, can predict protein structure. However, what i...
Resistance to androgen receptor inhibitors remains a primary challenge in prostate cancer treatment, yet identifying synergistic co-therapies is hindered by immense combinatorial search spaces and the limited interpretability of predictive computatio...
Accurate prediction of gene fusion pathogenicity is critical for understanding oncogenic mechanisms and advancing precision oncology. While existing computational methods provide valuable insights, their performance remains limited by incomplete inte...
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