11 papers · ranked by Valyu relevance
Maddalena M Bolognesi, Lorenzo Dall’Olio, Giulio Eugenio Mandelli, Luisa Lorenzi + 7 more
Lymph nodes (LN) are key secondary lymphoid organs (SLO) for a coordinated immune response. They have been extensively characterized by numerous investigative techniques chiefly as single cell suspensions because they are composed of vagile yet crowded hematolymphoid elements, unfriendly to spatial tissue…
Kini Chen, Mohammad Torabi, Jie Jian, Archer Y. Yang + 1 more
Dynamic functional connectivity (dFC) studies the time-varying coordination between brain regions measured with fMRI and is a potential biomarker for understanding cognitive dynamics and tracking the development of neurological disorders. However, a critical methodological challenge lies in the variability of dFC…
Diya Ramani
Rare diseases collectively affect over 300 million individuals worldwide, yet the vast majority lack approved pharmacological treatments, leaving patients with few therapeutic options and researchers with limited computational tools for systematic candidate identification. This study presents a network-based…
Daniel M. Gonçalves, André Patrício, Rafael S. Costa, Rui Henriques
The growing availability and complexity of omics data have driven the development of specialized algorithms for modeling molecular systems. Although graph-based learning methods effectively represent biological interactions, they often neglect the statistical information embedded in node and edge annotations. To…
Katyayni Ganesan, Elisa Billard, Tom L. Kaufmann, Cody B Strange + 4 more
Phylogenetic trees play a fundamental role in elucidating evolutionary relationships among taxa. Clustering taxa remains a major challenge across diverse biological domains such as cancer genomics, microbial systematics, and phylogenomics. Several methods partition taxa in phylogenetic trees into clusters, but these…
Paul Chon, William B. Andreopoulos
Protein language models (PLMs) are shown to be powerful predictors of protein structure and function but their internal mechanisms remain poorly understood. Recent mechanistic interpretability methods have decomposed PLM representations into interpretable features, but they have not combined methods on a single…
Miguel D. Fernández-de-Bobadilla, Val F. Lanza
Bacterial strain typing is key to surveillance, outbreak investigation and microbial ecology, yet current systems remain species-specific, reference-dependent and lack a universal, interpretable metric of genomic relatedness. Here, we introduce BacTaxID, a fully configurable, whole-genome k-mer-based framework that…
Claudia Montufar Leon, Yao Wang, Frank Britto Bisso, Arya Mehta + 1 more
The CRISPR-dCas9 system has emerged as a versatile platform for programmable gene regulation, offering unique advantages in modularity and orthogonality for constructing synthetic genetic circuits. Here, we present a novel architecture for biomolecular neural networks based on dCas9, guide RNAs, and antisense RNA…
Luis J. Vidal, Joan Carles Pons, Mateus B. Fiamenghi, Nikos Kyrpides + 1 more
Rapid expansion of viral sequence data demands classifiers that scale, track ICTV updates, and provide interpretable evidence. We present VPF-Class 2.0, an updated successor to VPF-Class, centred on the taxonomic classification, that retains marker-driven protein domain detection but replaces rule-based voting with a…
Caroline L. Alves, Simone Hufgard, Margot Mayer, Helena Dasch + 4 more
To address the limitations of calcium imaging data, we propose a segmentation-agnostic deep learning framework that integrates Quantile-Based Time-Series Network (QTN) representations with convolutional neural networks to classify neuronal dynamics across multiple spatial resolutions and acquisition frequencies. By…
Setareh Rahimi, Stephen Bonner, Avid Afzal, Marta Milo + 2 more
Predicting gene essentiality across cellular contexts is a central challenge in computational biology, with implications for identifying cancer vulnerabilities. Graph neural networks (GNNs) integrate molecular interaction networks with gene-level features, but it remains unclear whether their performance gains arise…