optimal transport

This paper introduces a computational framework to model core carbon metabolism across the lifecycle of Arabidopsis thaliana, showing agreement with experimental data and enabling lifecycle metabolic studies.

This study uses optogenetics to control membrane polarization and shows it increases calcium entry through TRPV2 channels, promoting cell migration in C2C12 cells.

The paper introduces a linear deconvolution method using optimal transport to improve accuracy in mass spectrometry by reducing sensitivity to measurement inaccuracies.

This paper uses goal attainment optimization to design a modular chassis cell for efficient production of diverse products through metabolic engineering.

This paper introduces an optimization algorithm for multichannel transcranial electric stimulation that maximizes focality while controlling field strength in targets, outperforming naive search methods.

This paper introduces r-deFBA, a framework that integrates metabolic dynamics, resource allocation, and transcriptional regulation for predicting cellular behavior over time.

This paper optimizes interferential stimulation (IFS) using electrode arrays to achieve focal brain stimulation, showing it can be more focal than conventional HD-TES but with lower intensity.

The paper develops an inverse problem approach to model neural function in Drosophila melanogaster using calcium imaging data and optimization algorithms.

This paper models the distance to delivering IRS implementation strategies in Zambia, finding that risk prioritization strategies vary in their distance estimates and do not necessarily correlate with remoteness.

This paper introduces ecFBA, an enzyme capacity-constrained flux balance analysis method, to improve flux prediction accuracy in CHO cells by incorporating enzyme kinetic data.

The paper identifies global terrestrial areas prioritized for conservation to maximize synergies between biodiversity, carbon retention, and water provisioning.

The paper develops an optimal control model of the compensatory eye movement system that successfully reproduces eye movement data across multiple conditions and explains non-linear reflex summation.

The paper develops a software package for selecting metabolic models using isotopologue data from SIRM experiments, demonstrating its effectiveness with UDP-GlcNAc datasets.

The paper uses a multiobjective optimization approach to study how neural networks degrade and regenerate over an organism's lifespan, finding Pareto optimal tradeoffs between computational error, connection cost, and regeneration rate.

This paper uses optimization-based modeling to study how sensory networks, specifically in the olfactory system, track low-dimensional latent representations of stimuli through temporal dynamics.

The paper shows that optimal control of visuomotor feedback responses can be simplified to a time-to-target dependent scheme, validated through experiments and models.

VG-Flow enables strain-aware full-length genome assembly from mixed samples using a de novo approach that improves contiguity and haplotype abundance estimation.

The paper develops a multi-scale conservation prioritization framework to identify global land areas needed for species protection, revealing uneven conservation burdens across countries.

The paper develops a high-throughput live cell system using optogenetics to screen voltage and Ca2+ sensors by modulating ion channels and cAMP levels.

AStarix provides a fast and optimal algorithm for aligning sequences to genome graphs, outperforming existing methods by 1-2 orders of magnitude.

The paper proposes a hybrid optimal contribution approach to balance short-term genetic gains with long-term sustainability in plant breeding programs.

This paper develops a method for targeted cell ablation in zebrafish embryos using optogenetic transcriptional control combined with genetically encoded toxins and cis-regulatory elements.

The paper investigates clustering with Gaussian Mixture Models under misspecification and high-dimensional data, showing EM outperforms GD in misspecification but GD is better for high-dimensional data, and introduces a penalty term using AD for improved clustering.

The paper introduces LocPL, a method that improves signaling pathway reconstruction from PPIs by incorporating protein localization data, resulting in more accurate and biologically meaningful reconstructions.

This study uses single-cell RNA-seq to analyze aging in mice, finding that cell identity has a greater influence on aging trajectories than tissue environment.

The paper introduces opt-SNE, an automated t-SNE parameter selection tool that improves visualization and analysis of large single-cell datasets by optimizing early exaggeration and gradient descent settings.

This study uses control-theoretic principles to optimize phage cocktail timing and composition for bacterial infection treatment, showing that two-phage cocktails can restore efficacy in immunodeficient hosts.

The paper identifies sensory neurons innervating lymph nodes and shows they modulate gene expression in endothelium, stromal cells, and innate leukocytes through direct communication.

This paper applies Pade-approximation based Differential Evolution to solve a nonlinear Hepatitis-B model, showing improved convergence and error performance compared to NSFD.