optimal transport

When Less Is Not More: DICEPro Mitigates the Impact of Incomplete Reference Matrices on Cellular Frequency Deconvolution.

The paper evaluates deconvolution methods' robustness to incomplete reference matrices and introduces DICEPro to improve performance by adjusting reference signatures.

SIMOFF: Discovering the metabolic objective of the cell

SIMOFF infers metabolic objectives from flux data, improving gene essentiality predictions in yeast and CHO cells.

Modeling development of tertiary lymphoid structures in pulmonary tuberculosis by 3D profiling and trajectory analysis

This study uses 3D reconstruction and optimal transport modeling to analyze TLS development in TB-infected lungs, revealing distinct maturation trajectories and spatial dynamics.

FALCON: Closed-Loop Multi-Objective Optimization of Lipid Nanoparticles for Cell-Selective mRNA Delivery

FALCON optimizes lipid nanoparticles for cell-selective mRNA delivery, improving transfection efficiency and selectivity in vivo.

Functional Templates in fMRI: Building Accurate and Interpretable Group-Level Decoders

This paper compares functional alignment methods and template construction strategies in fMRI to improve group-level decoding accuracy and interpretability.

DivQuant: Estimation of Species Richness and Entropy from Small Samples

DivQuant estimates species richness and entropy from small samples, achieving accurate confidence intervals and outperforming existing methods across multiple datasets.

A New Hybrid Method for Brain Tumor Detection Based on Deep Learning

This paper introduces a hybrid DCNN-WOA framework for brain tumor detection and classification, achieving high accuracy and outperforming existing methods on an MRI dataset.

VelOT: kinetic-free RNA velocity inference via optimal transport, flow-field smoothing, and VAMP coarse-graining of cellular dynamics

VelOT improves RNA velocity inference by using optimal transport and flow-field smoothing, outperforming existing methods in directionality and coherence.

Reachability-Preserving Minimum Edge Cut Problem and Applications in Biology

The paper introduces the Reachability Preserving Minimum Edge Cut problem to model biological pathway interventions, showing when fast algorithms work and when exact methods are needed.

Recursive exploration of metabolic yield space

This paper introduces a novel method for efficiently generating yield spaces from genome-scale metabolic networks, enabling advanced analysis techniques for metabolic modeling.

Effect-oriented automated muscle path modeling via gradient-specified optimization using muscle surface mesh and moment arm

This study introduces an automated muscle path modeling approach that optimizes paths to match anatomical and biomechanical constraints, producing realistic results efficiently.

Optogenetic cross-linking of the actin cytoskeleton using DARPins

This paper introduces an optogenetic system using DARPins to reversibly control actin cross-linking in living cells, showing inhibition of cell traction forces upon light activation.

Cell Trajectory Inference based on Optimal Transport and a mechanistic stochastic gene expression model

This paper introduces a method for cell trajectory inference using optimal transport with a mechanistic stochastic gene expression model, showing the Bursty model better captures gene dynamics than the Diffusive model.

RhoG, Rac1 and Cdc42 cooperation in cell protrusion revealed bymultiplexed optogenetics and biosensor imaging

This study uses optogenetics and biosensor imaging to show RhoG activates Rac1 and Cdc42 in cell protrusion, with RhoG's effects on protrusion partially mediated by Rac1 and some independent of it.

Optogenetic activation of liver-innervating vagal sensory neurons increases anxiety-like behavior in mice.

This study shows that optogenetic activation of liver-innervating vagal sensory neurons increases anxiety-like behavior in mice by activating the NTS-LC circuit.

Reconstructing True 3D Spatial Omics at Single-Cell Resolution

This paper introduces a computational framework for true 3D spatial reconstruction of tissues, demonstrating improved fidelity over 2D methods across multiple spatial omics modalities.

Metabolic Coherence of the Mouse Brain

The paper maps spatial metabolome coherence across mouse brain regions using MALDI imaging and optimal transport, showing preserved coherence in Alzheimer's model despite metabolic changes and demonstrating intervention effects.

Model-supported patient stratification using multi-objective synergy optimization in combination therapy

This paper develops a method to stratify patients for combination therapy by optimizing synergy across efficacy and potency, using a preclinical mouse dataset to demonstrate subgroup-specific treatment responses.

Optimized optogenetic anti-CRISPR for endogenous gene regulation in Drosophila

This paper develops an optimized optogenetic system using Acr proteins to regulate endogenous gene expression in Drosophila with improved light sensitivity.

Hybrid genome-scale modeling and machine learning reveal cost-efficient strategies for phototrophic PHB production in Rhodopseudomonas palustris

This paper combines genome-scale modeling, machine learning, and thermodynamics analysis to identify cost-effective strategies for PHB production in Rhodopseudomonas palustris.

CHAMPOLLION: Robust Multi-Omics Integration via Inverse Optimal Transport Using Paired Cells

CHAMPOLLION improves multi-omics integration by using regularized optimal transport to align unpaired cells and reveal cross-modal relationships, outperforming existing methods with fewer paired cells.

Parallel algorithms for phylogenetic inference under a structured coalescent approximation

The paper introduces parallel algorithms to improve the computational efficiency of structured coalescent models for phylogeographic analysis, enabling faster and larger-scale studies of pathogen spread.

SPaCeD: Spatial Point Process Distances for Pairing the Heavy and Light Chains of B Cell Receptors from Spatial BCR-seq

SPaCeD improves heavy-light chain pairing accuracy in spatial BCR-seq by integrating expression matrices with spatial distances via optimal transport.

Bi-level diversity optimisation for representative protein panel selection

This paper introduces a bi-level diversity-optimization framework for selecting representative protein panels, reducing redundancy and improving diversity compared to existing methods.

DeepMapper: Attention-Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

This paper proposes a deep learning-based control framework for wound healing that accelerates closure by 17.71% in simulations and 40% in vivo.

Maximally Divergent Synonymous Gene Design with SIRIUS

SIRIUS generates maximally divergent DNA sequences for a given protein, reducing shared subsequences compared to existing methods.

Generalist method to reconstruct metabolic networks from multi-omics data at large-scale

The paper introduces SPECTRA, a method to reconstruct metabolic networks from multi-omics data at large-scale, improving speed and reaction inclusion across cancer cell lines, microbial reconstructions, and synthetic gut microbiota.

Synthetic budding morphogenesis by optogenetic receptor tyrosine kinase signaling

This paper uses optogenetic control of RET signaling to induce controlled budding in human kidney organoids.

Maximizing Nature-based Solutions using Artificial Intelligence to align global biodiversity, climate, and water targets.

This paper presents an AI framework to prioritize conservation and restoration actions that align biodiversity, climate, and water targets by optimizing habitat connectivity and co-benefits.

Optogenetic Control of the Integrated Stress Response Limits Glioblastoma Invasion

This study uses optogenetic ISR activation to show reduced glioblastoma invasion and migration, suggesting potential therapeutic strategies.