clustering

Major microbiota transitions across liver disease progression are mediated by key taxa linking host environments and microbial communities

The paper uses an energy landscape analysis framework to identify key microbial taxa linked to liver disease progression and host environments.

SubCortexMesh: A Python toolbox for surface-based analysis of subcortical brain regions

SubCortexMesh provides a Python toolbox for surface-based analysis of subcortical brain regions, enabling automated surface estimation and shape-related metrics computation.

An automated machine vision-based index for Rett Syndrome provides a generalizable framework for modeling rare disease therapeutics

This paper develops an automated machine vision-based index for Rett Syndrome that improves preclinical phenotyping by detecting disease-relevant behaviors and reducing animal use.

HiMaLAYAS: enrichment-based annotation and visualization of hierarchically clustered matrices

HiMaLAYAS, a Python package, cuts dendrograms, tests clusters for categorical annotation enrichment (hypergeometric, Benjamini-Hochberg FDR), and renders significant annotations beside clustered heatmaps in one workflow.

Physiological Aging and Cardiovascular Disease Distinctly Remodel the Human Cardiac Lymphatic Endothelium

This study identifies age- and disease-specific remodeling of cardiac lymphatic endothelial cells through single-nucleus transcriptomics and spatial analysis.

Biologically Informed Multi-Omics Integration Reveals Clinically Meaningful Patient Representations in Acute Myeloid Leukemia

This paper introduces SurvMOCA-GNN, a multi-omics integration framework that improves patient stratification in AML by incorporating biological networks and clinical data.

Smaller Genomes and Shorter Prophage Sequences Differentiate Clinical from Environmental Isolates of Pseudomonas aeruginosa

This study compares genome features of Pseudomonas aeruginosa isolates from cystic fibrosis patients and environmental sources, finding smaller genomes and shorter prophage sequences in clinical isolates.

Topologically-based parameter inference for agent-based model selection from spatiotemporal cellular data

The paper introduces TOPAZ, a framework that uses topological data analysis and Bayesian methods to infer agent-based models from spatiotemporal cellular data, showing it can accurately recover model parameters and distinguish between models.

Complex roles for a conserved two-component system in a honey bee symbiosis

This study identifies the conserved two-component system ChvGI as essential for the honey bee symbiont Bombella apis to survive in harsh host environments and regulate key bacterial behaviors.

Deep learning extracts MoA-specific signatures from high-throughput images of chemically and genetically perturbed Corynebacteria

This paper develops a deep learning model to identify drug modes of action from high-throughput images of chemically and genetically perturbed Corynebacteria.

Discovering Heterogeneous Neurodegenerative Disease Patterns From MRI Data for Improved Prediction

This paper introduces a mixture-of-experts framework for identifying clinically meaningful subtypes in neurodegenerative diseases, improving prediction of progression to Alzheimer's disease.

ClustSIGNAL identifies cell types and subtypes using an adaptive smoothing approach for scalable spatial omics clustering

ClustSIGNAL improves spatial transcriptomics clustering by adapting smoothing based on neighbourhood complexity, enabling scalable analysis of large datasets.

EISCA and EISTA: Full-Spectrum Pipelines for Single-Cell and Spatial Transcriptomics Analysis

EISCA and EISTA are pipelines for single-cell and spatial transcriptomics analysis that provide standardized, modular workflows for data processing and downstream analysis.

Benchmarking 16S rRNA gene amplicon analysis in high-diversity microbial communities reveals fundamental trade-offs in clustering and denoising

This study benchmarks 16S rRNA gene analysis pipelines in high-diversity datasets, revealing trade-offs between clustering accuracy, species recovery, and abundance reconstruction.

WHAT IS NORMAL? MULTIMODAL CHARACTERIZATION OF NON-DISEASED PEDIATRIC DUODENAL BIOPSIES USING MACHINE LEARNING IMAGE ANALYSIS AND TRANSCRIPTOMICS

The paper characterizes non-diseased pediatric duodenal biopsies across multiple domains, finding clinical and transcriptomic heterogeneity but limited histologic differences.

Loss of SEZ6L2 disrupts synaptic architecture and drives progressive behavioral deficits

This study characterizes Sez6l2 knockout mice, showing behavioral and synaptic deficits, and compares them to Sez6 triple knockout mice, highlighting SEZ6L2's non-redundant role in brain function.

Self-Supervised Discovery of Discrete Local States in Noisy Image Sequences

This paper introduces a self-supervised framework to discover discrete local states in noisy image sequences without clean targets or labels, achieving high precision in particle tracking and separating biological structures from artifacts.

Active Escape or Active Change? Decomposing Pavlovian Bias into Non-emotional Components

The paper decomposes Pavlovian bias into non-emotional components using a novel paradigm, showing that previously attributed emotional biases can be explained by transition and cue salience.

A repair-associated bronchial epithelial differentiation trajectory through KRT14+ basal and hillock-like cells drives airway inflammation and remodelling in childhood-onset asthma

The paper identifies a novel asthma-associated epithelial differentiation trajectory involving KRT14+ basal cells and hillock-like cells that contributes to airway inflammation and remodelling in childhood-onset asthma.

Spatial Transcriptomics Identifies Muscle Inflammation Susceptibility as a Distinct Periarticular Skeletal Muscle Phenotype in End-Stage Knee Osteoarthritis

Subacute effects of ketamine on neural correlates of reward processing

This study examines ketamine's subacute effects on reward processing using fMRI and finds no significant modulation of neural activation during the MID task five hours post-infusion.

Short-term BDD treatment of wastewater effluent reveals dissolved oxygen turnover and microbial community restructuring

This study examines the short-term effects of BDD electrochemical treatment on wastewater effluent, showing changes in dissolved oxygen and microbial community structure without major physicochemical shifts.

Encoding of bimanual movement directions across the human sensorimotor system

The paper investigates how the brain encodes bimanual movement directions using fMRI, finding distinct neural representations for unimanual and bimanual movements.

Spike Sorting with VanillaSort

VanillaSort improves spike sorting by combining multichannel detection with template-guided clustering, outperforming SimSort on real-data benchmarks.

Late lactation represents the main window for sow-to-piglet transmission of persistent gut strains

Long-read 16S-ITS-23S tracking in 17 sow-piglet families shows maternal putative-strain sharing peaks in late lactation, which supplies most maternally derived strains persisting post-weaning.

In utero barcoding of mouse mesoderm reveals the clonal architecture of organ mesenchyme

The paper uses in utero barcoding and single-cell transcriptomics to map clonal relationships in mouse mesoderm-derived tissues, revealing lineage relationships in liver and heart mesenchyme.

Dynamic social envirotypes demonstrate adolescent brain dysconnectivity is contextual

The paper identifies dynamic social envirotypes in adolescents and shows how brain connectivity patterns vary with social context, affecting mental health outcomes.

A knockout screening platform for interferon-stimulated genes in respiratory cells identifies LY6E as a dominant antiviral effector against coronaviruses

This study uses CRISPR-Cas9 to identify LY6E as an antiviral factor against coronaviruses in respiratory cells.

High-resolution postmortem MRI of the human infant brain: cortical reconstruction and anatomical parcellation

This paper introduces a computational framework for automated anatomical segmentation and cortical reconstruction in high-resolution postmortem infant MRI, showing improved performance across diverse datasets.

Spatial Transcriptomics Reveal Developmental Dynamics of the Human Cerebral Cortex and Striatum

This study uses spatial transcriptomics and snRNA-seq to identify 25 forebrain regions and characterize dynamic changes in the human fetal cortex and striatum during late first and early second trimesters.