optimal transport

scSAGA: Single-cell Sampled Gromov Wasserstein Alignment for Scalable and Memory-efficient Integration of Multi-modal Single Cell Data

scSAGA improves multimodal single-cell data integration by preserving geometry and scaling efficiently, outperforming existing methods on various datasets.

Topography Aware Optimal Transport for Alignment of Spatial Omics Data

TOAST improves spatial omics data alignment by integrating spatial constraints into optimal transport, enhancing accuracy and biological interpretability.

Why phylogenies compress so well: combinatorial guarantees under the Infinite Sites Model

The paper explains why phylogenetic compression works well by introducing a formal framework and showing that Neighbor Joining achieves near-optimal compression under the Infinite Sites Model.

Multi-objective optimization-based design of a compliant gravity balancing orthosis: development and validation

This paper develops a multi-objective optimization framework for designing a compliant gravity balancing shoulder orthosis, validated through mechanical testing and in-vivo muscle activity reduction in healthy individuals.

FASTERCC: Accelerating Flux Consistency Testing and Context-Specific Reconstruction for Large-Scale Metabolic Network Models

FASTERCC improves metabolic network analysis by accelerating flux consistency testing and reconstruction, reducing runtime by 20-fold for large networks.

MICA: Model-Informed Change-point Analysis

MICA detects change points by minimizing the discrepancy between model simulations and observed data, demonstrating utility in epidemiological modeling and system monitoring.

GOTFlow: Learning Directed Population Transitions from Cross-Sectional Biomedical Data with Optimal Transport

GOTFlow infers directed population transitions from cross-sectional biomedical data using optimal transport, revealing biologically meaningful dynamics in endometrial remodelling, breast cancer risk, and prion disease.

Branch Length Transforms using Optimal Tree Metric Matching.

This paper introduces a method to match branch lengths between trees, improving accuracy in phylogenomic analyses by addressing the challenges of heterogeneous branch length measurements.

Modeling Multi-Modal Brain Connectomes for Brain Disorder Diagnosis via Graph Diffusion Optimal Transport Network

This paper introduces GDOT-Net, a graph diffusion optimal transport network that aligns structural and functional brain connectivity for improved diagnosis of neuropsychiatric disorders.

Toroidal Search Algorithm: A Topology-Inspired Metaheuristic with Applications to ODE Parameterization in Mathematical Oncology

This paper introduces the Toroidal Search Algorithm (TSA), a metaheuristic optimization method that outperforms existing techniques in high-dimensional and bounded search spaces, with applications in mathematical oncology parameter estimation.

Towards building a World Model to simulate perturbation-induced cellular dynamics by AlphaCell

AlphaCell simulates perturbation-induced cellular dynamics by addressing limitations in current models through three innovations: latent manifold rectification, biological reality reconstruction, and universal state transition.

The dynamic response of the bacterial flagellar motor to its direct intracellular input signal

This paper demonstrates that activation of 1-3 CheY-P molecules is sufficient to switch the bacterial flagellar motor from CCW to CW, resolving a long-standing paradox about chemotactic sensitivity.

Displacement-Optimized Tanglegrams for Trees and Networks

The paper introduces a new method for visualizing phylogenetic trees and networks by minimizing taxon and reticulate displacement, showing improved performance over existing approaches.

GALA: A Unified Landmark-Free Framework for Coarse-to-Fine Spatial Alignment Across Resolutions and Modalities in Spatial Transcriptomics

GALA provides a landmark-free framework for spatial alignment across resolutions and modalities in spatial transcriptomics, improving accuracy and efficiency.

Multiobjective design of growth media with genome-scale metabolic models and Bayesian optimization

This paper introduces gsMOBO, a computational method that uses genome-scale metabolic models and Bayesian optimization to design cost-effective and productive culture media by optimizing nutrient combinations across high-dimensional spaces.

Optimal transport fate mapping resolves T cell differentiation dynamics across tissues

This paper uses optimal transport to map CD8 T cell differentiation across time and tissues, revealing distinct migration waves and gene regulatory programs.

A Systems-Level Framework Integrating Geometry-Controlled Plasmonics, AI-Driven Molecular Kinetics, and Organoid Validation for Next-Generation Biosensing

This paper introduces a systems-level framework combining plasmonic nanosensors, AI-driven molecular kinetics, and organoid validation to enhance biosensing capabilities.

OT-Fusion: Cortex-conditioned Fusion of Matched PET and MRI Images Using Optimal Transport

OT-Fusion maps PET metabolic activity onto MRI cortical structures using optimal transport, improving image quality and localization for neurological assessments.

Optimizing and assessing multichannel TMS focality

This study develops a framework to optimize and assess multichannel TMS focality, showing mTMS systems can achieve performance comparable to single-channel TMS for deeper cortical targets.

The Electromagnetic-Core-First Paradigm: A Mechatronic Co-Design Framework for High-Density Implantable Systems

This paper introduces the Electromagnetic Core-First framework to resolve design conflicts in implantable mechatronic systems, achieving high performance and biocompatibility in a miniaturized blood pump.

SPCoral: diagonal integration of spatial multi-omics across diverse modalities and technologies

SPCoral integrates spatial multi-omics data across different modalities and technologies, improving spatial domain identification and cross-modal analysis.

EvoPool: Evolution-Guided Pooling of Protein Language Model Embeddings

EvoPool improves variant effect prediction by integrating evolutionary information into protein language model embeddings using optimal transport.

Intracellular targeting of a light-activated GPCR elicits spatially selective signalling

This study uses an optogenetic platform to activate a GPCR at different intracellular membranes, showing location-dependent transcriptional responses.

Context-Aware Protein Representations Using Protein Language Models and Optimal Transport

COPTER improves protein representation by incorporating context using optimal transport, achieving better performance in drug target and perturbation response predictions.

Optimizing electrode placement and information capacity for local field potentials in cortex

This paper introduces tools to optimize electrode placement and maximize information capacity for local field potentials in the cortex using subject-specific modeling.

Functional interrogation uncovers a critical role for a high-plasticity cell state in lung adenocarcinoma

In vivo lineage tracing and targeted ablation in autochthonous mouse lung adenocarcinoma establish the Slc4a11+ high-plasticity cell state as a bidirectional transition hub driving tumor progression and therapy resistance.

BiLO: Bilevel Local Operator Learning for PDE Inverse Problems

The paper introduces BiLO, a neural network method for solving PDE inverse problems by formulating them as bilevel optimization problems, showing it enforces PDE constraints and handles noisy data effectively.

Multi-objective optimization for designing structurally similar proteins with diverse sequences

Computational Approaches in Chemical Space Exploration for Carbon Fixation Pathways

The paper uses graph-based cheminformatics and ILP optimization to explore chemical space for carbon fixation pathways, identifying new enzymatic cascades and autocatalytic cycles.

Predicting single-cell responses to novel genetic perturbations with optimal transport

This paper introduces an optimal transport-based method to predict single-cell transcriptional responses to novel genetic perturbations, showing competitive performance on benchmark datasets.