clustering

Identification and characterization of new P. aeruginosa phages using a surface receptor platform

The paper introduces a SURFAR platform to identify and characterize new P. aeruginosa phages by targeting specific receptors, isolating two novel phages with distinct host ranges.

Functional Data Clustering of Filopodia Dynamics

The paper clusters filopodia dynamics using functional data analysis to identify distinct temporal patterns linked to Notch signaling in fruit fly development.

DisCell: Separating Spillover from Niche Response in Spatial Transcriptomics

DisCell identifies and separates spillover from niche responses in spatial transcriptomics data, confirming a previously reported finding about esophageal cancer cells.

From Fill to Freeze: Redesigning homeRNA to Enable Robust Sampling and Scalable Downstream Processing Workflows for Remote Blood Transcriptomics

This paper validates the redesigned homeRNA platform's robustness to remote study stresses, showing it maintains RNA quality under varied conditions and storage times.

Genomic signatures distinguish isolates of Salmonella Typhimurium from humans and livestock

The paper distinguishes human and livestock-associated Salmonella Typhimurium isolates using genomic signatures and machine learning.

Multimodal cellular context enables molecular phenotyping from single-molecule trajectories

The paper introduces MIST, a framework that integrates single-molecule trajectory data with cellular context to improve molecular phenotyping in E. coli.

Widespread Saccharomyces hybridization in agave fermentations arises repeatedly from asymmetric parental diversity

The paper identifies widespread Saccharomyces hybridization in agave fermentations, showing multiple independent origins and asymmetric parental genetic diversity.

Multi-Criteria Evaluation of Hibiscus mutabilis Cultivars for Food Development Using Delphi and Analytic Hierarchy Process

This study evaluates 11 Hibiscus mutabilis cultivars for food use using Delphi and AHP, identifying three top cultivars for food development.

SOPSim: A cell vertex-based application for simulating sensory bristle patterning with dynamic filopodia

This study introduces SOPSim, a simulation tool that models sensory bristle patterning in fruit flies by incorporating filopodia dynamics and Notch signaling.

Breaking the bottleneck: semi-automated quantification of actin filament dynamics

The paper introduces SMAUG, a semi-automated tool for analyzing actin filament dynamics from TIRF microscopy images, reducing analysis time while maintaining accuracy.

scCont: Interpretable Contrastive Learning for Functional Characterization of Cellular State Transitions

scCont is an unsupervised contrastive learning framework that extracts interpretable functional transition units from scRNA-seq data, outperforming baseline methods in capturing biologically meaningful dynamics.

Genomic analysis of the Streptococcus anginosus group; taxonomic implications, evolutionary insights and clinical considerations

This study uses genomic analysis to reclassify the Streptococcus anginosus group into four taxa, revealing diversity and lineage-associated traits linked to invasive disease.

Sex differences in agonistic social behavior: Effects of exercise and ovariectomy

This study examines how sex, exercise, and ovariectomy affect offensive and defensive aggression in rats, finding sex-specific behavioral differences and no effect of exercise.

Deducing splicing events from transcript sets with splicelogic

splicelogic converts transcript-set comparisons into interpretable splicing events, enabling downstream analysis of isoform changes in RNA-seq data.

Rapid, accurate, and memory-frugal sub-gene-level quantification of probe-based, multiplexed single-cell data

This paper introduces simpleaf, a tool for efficient sub-gene-level quantification of probe-based single-cell data, showing improved speed and memory use compared to existing tools.

siRNA/mRNA payload of lipid nanoparticles quantified using fluorescence microscopy and correlation spectroscopy

The paper quantifies mRNA and siRNA payload in lipid nanoparticles using fluorescence microscopy and FCS, showing size-dependent payload and coencapsulation dynamics.

SNAzzy: an image processing pipeline for investigating global Synchronous Network Activity

SNAzzy processes and analyzes high-throughput microscopy data from Drosophila embryos to study synchronous network activity.

Automahout: an autonomous image analysis system for cell tracking

Automahout autonomously tracks cells in time-lapse images using a self-tuning system that annotates, trains, and refines models without human input, achieving high TRA scores on public datasets.

Clinical relevance of diffusion tensor imaging-based parameters estimated with deep learning: the effect of model retraining

This study evaluates how retraining deep learning models affects the statistical consistency of diffusion tensor imaging parameters in bipolar disorder, showing significant variability across models.

Integrative identification of Tetratostichococcus sp. CCAH0201 (Trebouxiophyceae, Chlorophyta) from Rhizophora leaves in the Can Gio Mangrove Forest, Vietnam

The paper identifies a microalgal strain from mangrove leaves using molecular markers and phylogenetic analysis, placing it closely related to Tetratostichococcus jenerensis.

RadMultiBench: A Reproducible Dual-Task Benchmark Exposing the Limits of Pre-Trained Vision-Language Models Across Thoracic and Breast Imaging

RadMultiBench evaluates pre-trained vision-language models on medical imaging tasks, showing performance gaps in report generation and classification across thoracic and breast imaging.

Extended Pavlovian conditioned approach training and devaluation in Long-Evans rats using time-restricted feeding

This study develops an extended Pavlovian conditioned approach paradigm in Long-Evans rats under time-restricted feeding to better identify phenotypes linked to compulsive behaviors and stress-related dysregulation.

Towards an analytical framework for investigating the neurophysiological influence of social context in speech perception

The paper introduces a framework combining a fine-tuned LLM and TRFs to isolate social context's influence on speech perception, showing social context improves EEG prediction.

Geometric Morphometrics of Pistillate Flowers in Astrocaryum sect. Huicungo (Arecaceae): Taxonomic Implications for the Peruvian Species

This study uses geometric morphometrics to analyze pistillate flower shapes in Peruvian Astrocaryum species, revealing taxonomic insights through quantitative shape analysis.

The C. elegans Connectome Toolbox: an open, extensible framework for multimodal connectomic data integration and analysis

The paper introduces the C. elegans Connectome Toolbox, a framework for integrating and analyzing multimodal connectomic data, enabling comparison across datasets and modalities.

Evaluating State-Transition Models in Short Resting-State fMRI with Continuous-Dynamics Controls

This study compares hidden Markov models (HMMs) and vector autoregressive (VAR) models in resting-state fMRI to determine if apparent state transitions reflect discrete dynamics or continuous activity, finding that VAR often outperforms HMMs in continuous cases.

A comparative transcriptomic framework across kidney organoid, assembloid, and transplantation models

The paper compares transcriptomic profiles across kidney organoid, assembloid, and transplantation models to evaluate their maturity and suitability for research.

Variation in the embryonic cell lineages of Caenorhabditis elegans natural populations

The paper quantifies developmental variation in C. elegans natural populations using embGAN, finding genotype-specific differences in cell-cycle timing that exceed within-strain variation.

Live attenuated YFV-17D vaccine induces robust B and T cell immunity in vaccine-draining lymph nodes

This study examines immune dynamics in lymph nodes after YFV-17D vaccination, identifying robust B and T cell responses and a conserved germinal center program across different vaccines.

Common attentional mechanisms, but distinct computational dynamics, across Statistical and Reward Learning

This study compares statistical and reward learning, finding shared attentional mechanisms but distinct computational dynamics in neural representations and learning rates.