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... read more
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... read more
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... read more
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... read more
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... read more
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... read more
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... read more
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... read more
Background: Early diagnosis of dementia can significantly improve care planning and patient outcomes while delaying progression. Machine learning algorithms can identify patterns in clinical and neuroimaging data that may aid in the early detection o... read more
Autism spectrum disorder (ASD) affects a substantial proportion of children worldwide, yet clinical assessment of symptom severity remains resource-intensive and unevenly accessible. Artificial intelligence (AI) has transformative potential to suppor... read more
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