9 papers · ranked by Valyu relevance
Jackie Rao, Muntadher Jihad, Giulia Biffi, Paul D.W. Kirk
Identifying cell types from single-cell RNA sequencing (scRNA-seq) data typically requires several separate and often uninterpretable steps: dimensionality reduction, batch-correction, clustering, marker-gene identification and the discovery of finer-grained structure. Here we introduce scFLAME (single-cell Factor…
Mathias Claeys, Neil Fam, Xiaojiao Xiao, Tejas Vyas + 10 more
Background Patient selection for transcatheter mitral valve edge-to-edge repair (MTEER) remains challenging, particularly in individuals with complex mitral valve anatomy. Conventional risk scores incorporate limited clinical variables and do not adequately account for detailed echocardiographic features, resulting in…
Zichao Jin, Jiaoru Wang, Wenjiang Huang, Jingcheng Zhang + 2 more
Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework.…
Yilan Wu, Dun Jack Fu, Yukun Zhou, Siegfried K Wagner + 2 more
Background Large language model (LLM) agents capable of generating and executing statistical code from natural language may broaden access to clinical data analysis, yet which pipeline stages they perform reliably and which require expert oversight remain poorly defined. Objective This study aimed to evaluate the…
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
Dianzhuo Wang, Qian Xu, Arjun Banerjee, Rishi Jain + 7 more
Inferring biological function from experimental data is central to understanding emerging pathogens and developing effective countermeasures, yet interpreting these data remains slow and expert-intensive. AI agents could help accelerate this process by reasoning across sequence, structural, and biophysical evidence. We…
Sahar Alkhaibari, Feng Dong
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent difficulties in social communication, social interaction, and repetitive behaviors. Early and accurate diagnosis is essential but is often hindered by subjective clinical assessments, limited data availability, and…
Peter Gill, Helen Johannessen, Christine Børsum, Ane Elida Fonneløp + 1 more
DNA findings on clothing are often evaluated at sub-source level to address whether a person contributed DNA to a sample. In many cases, however, the disputed issue is not whose DNA is present, but how the DNA was transferred. This paper applies the HaloGen framework to evaluate DNA findings on stockings under…
Huihai Wu, Ashleigh Lister, Iain Macaulay, Katie Long + 10 more
Single-cell and spatial transcriptomics are transforming our understanding of cellular heterogeneity and tissue organization, yet their analytical complexity remains a major bottleneck. Here, we present EISCA and EISTA, two standardized, end-to-end pipelines for single-cell RNA- seq and imaging-based spatial…