trajectory inference

Modeling a Shared Reality of Tractography through Varied Structural Imaging

This paper introduces a method to generate white matter tractograms from FLAIR images without diffusion data, showing it captures structural probabilities similar to diffusion-based tractography.

muat: portable transformer-based method for tumour classification and representation learning from somatic variants

The paper introduces muat, a transformer-based tool for tumour classification using somatic variants, achieving high accuracy across different cohorts without retraining.

Single-cell trajectories in metastatic urothelial carcinoma reveal tumor-immune reprogramming and macrophage-driven resistance to PD-(L)1 blockade

This study uses single-cell RNA sequencing to analyze metastatic urothelial carcinoma and identifies macrophage-driven resistance to PD-(L)1 blockade as a key mechanism.

Decomposing representational drift across wake and sleep

This study decomposes representational drift in mice olfactory cortex during wake and sleep, showing distinct transformations driven by each state.

Tumor-immune trajectory context connects static tissue architecture to clinical outcomes

This paper introduces a trajectory-centric framework to model dynamic tumor-immune interactions, showing that treatment-phase TME states predict immunotherapy response better than pre-treatment states.

Digital Twins for Fungal Computing: Viable XOR Regimes, Parameter Inference, and Waveform-Guided Rediscovery

This paper develops a digital-twin framework for fungal excitable networks to identify viable XOR computation regimes and refine biophysical parameters using waveform matching.

Generating and navigating single cell dynamics via a geodesic bridge between nonlinear transcriptional and linear latent manifolds

GeoBridge transforms sparse scRNA-seq data into a continuous landscape for reconstructing and navigating cellular state transitions.

Specialized high-capacity mitochondria fuel cell invasion

The paper identifies specialized high-capacity mitochondria in C. elegans anchor cells that generate elevated ATP to fuel basement membrane invasion.

Adoption of MMPose, a general purpose pose estimation library, for animal tracking

This paper benchmarks pose estimation models for animal tracking using MMPose, finding trade-offs between accuracy and speed and highlighting the need for diverse training data.

Kainate receptors are critical for permissivity to sustained, disorganized, and network-wide pathological activity in the epileptic dentate gyrus

This study shows that kainate receptors (KARs) enable sustained pathological activity in the epileptic dentate gyrus by altering network dynamics and promoting disorganized firing patterns.

Genomic mosaicism reveals developmental organization of trunk neural crest-derived ganglia

The paper uses genomic mosaicism to study clonal dynamics of trunk neural crest-derived ganglia, finding conserved developmental patterns across species.

Deficits in forelimb reach learning in a mouse model of Fragile X syndrome

This study investigates motor learning deficits in Fmr1 KO mice, showing that reward cues alleviate some impairments and identifying specific behavioral parameters linked to learning success.

Temporal AI model predicts drivers of cell state trajectories across human aging

The paper introduces a temporal AI model, MaxToki, trained on extensive gene data to predict cell state changes across human aging and identifies age-modulating targets.

Single-cell RNA sequencing of peripheral blood cells identifies transcriptomic signatures in Parkinson's disease

This study uses single-cell RNA sequencing to identify immune cell-specific gene expression signatures and sex differences in Parkinson's disease patients compared to healthy controls.

MoCoO: Momentum Contrast ODE-Regularized VAE for Single-Cell Trajectory Inference and Representation Learning

MoCoO improves single-cell trajectory inference by combining VAE, Neural ODE, MoCo, and Flow Matching, achieving top performance in clustering and embedding quality across multiple datasets.

Systems analysis of ribosomal CAR-site dynamics

The paper introduces an analysis pipeline using mdsa-tools to study ribosomal CAR-site dynamics through molecular dynamics simulations and unsupervised learning.

Individual connectome fingerprints reveal early stabilization and long-term circuit remodeling after stroke

This study tracks how brain connectivity patterns change after stroke, showing early stabilization of functional fingerprints and long-term circuit remodeling that predicts recovery outcomes.

Keeping time with the host: reconstructing the developmental rhythms of malaria parasites

This study models malaria parasite development and sequestration in vivo using time series data from Plasmodium chabaudi, showing parasites adjust their development to host rhythms at a cost to multiplication rates.

Zero-shot reconstruction of mutant spatial transcriptomes

This paper introduces a zero-shot framework to predict spatial transcriptomes of mutants using single-cell RNA sequencing data without requiring spatial reference atlases.

An Intermediate Mesoderm Premyogenic Niche Supports Early Human Myogenic Lineage Progression

This paper identifies an intermediate mesoderm niche that supports early human myogenic lineage progression through BMP7 and laminin signaling, and shows the role of SIX1-EYA3 activity in this process.

Long-term clonal analysis using stochastic models reveals heterogeneity and quiescence of hematopoietic stem cells

The paper uses stochastic models to analyze clonal data from non-human primates, showing that HSC heterogeneity and quiescence are critical for long-term hematopoiesis.

Task-specificity of local load feedback depends on intersegmental information in an insect walking system

The study shows that load proprioceptive feedback in stick insects has direction-dependent effects on motor neuron activity during stepping, influenced by intersegmental signals.

Autophagy Dysfunction in iPSCs-Derived Neurons and Midbrain Organoids Carrying a SNCA Triplication

This study uses iPSC-derived neurons and midbrain organoids with SNCA triplication to show autophagy defects correlate with -Synuclein pathology and neuronal loss in Parkinson's disease.

Shape2Fate: a morphology-aware deep learning framework for tracking endocytic and exocytic carriers at nanoscale.

Shape2Fate tracks and classifies exocytic and endocytic carriers in live cells using morphology-aware deep learning, revealing pathway-specific exo-endocytic coordination rules.

Bayesian inference of tissue-migration histories in metastatic cancer from cell-lineage tracing data

This paper introduces BEAM, a Bayesian framework for inferring tissue migration histories in metastatic cancer from lineage tracing data, showing improved performance over existing methods.

Autophagy-Dependent Regulation of YAP1 by STK38 Governs Recruitment of Differentiated Cells as Progenitor Cells During Regeneration

The paper identifies STK38 as a YAP1 kinase that regulates paligenosis by autophagy-dependent degradation, enabling differentiated cells to act as progenitors during tissue regeneration.

Kilohertz-rate two-photon voltage imaging of population dynamics in vivo

This paper introduces HS2PM, a two-photon microscope that enables kilohertz-rate imaging of neuronal populations in vivo, revealing voltage dynamics and their role in sensory adaptation and population coding.

Time-Varying Dynamic Causal Modelling for Sequential Responses: Neural Mechanisms of Slow Cortical Potentials, Preparation, Planning and Beyond

This paper introduces DCM-SR, a new framework for modeling time-varying neural dynamics, and applies it to study slow cortical potentials in cognitive tasks.

Physics-constrained neural ordinary differential equation models to discover and predict microbial community dynamics

The paper introduces a physics-constrained neural ordinary differential equation model to predict microbial community dynamics and interactions, outperforming existing mechanistic and machine learning approaches.

Deep-learning-enabled morphodynamic analysis of drug responses in a biomimetic fibrin-based 3D glioblastoma invasion model

This paper develops a 3D glioblastoma model with deep learning to predict drug responses and invasion patterns.