optimal transport

Identifying Drug Sensitivity Subnetworks with NETPHIX

NETPHIX identifies mutated subnetworks associated with drug response by leveraging network properties and integer linear programming, revealing novel gene modules linked to MEK1/2 inhibitor sensitivity.

KOPTIC: A novel approach for in silico prediction of enzyme kinetics and regulation

KOPTIC predicts enzyme kinetics and regulation using in silico data, achieving high correlation with input flux data and identifying regulatory interactions.

A Novel Optimization-Based Tool to Automate Infeasible Cycle-Free Gapfilling of Genome-Scale Metabolic Models

This paper introduces OptFill, a tool for automated gapfilling of genome-scale metabolic models that avoids thermodynamically infeasible cycles, applied to both fictional and published models.

Ongoing surveillance protects tanoak whilst conserving biodiversity: applying optimal control theory to a spatial simulation model of sudden oak death

This paper applies optimal control theory to a spatial simulation model of sudden oak death to identify effective disease management strategies that protect tanoak while conserving biodiversity.

Network-based clustering for drug sensitivity prediction in cancer cell lines

This study introduces a network-based method combining optimal mass transport and machine learning to predict drug sensitivity in cancer cell lines by clustering genomic and chemical features.

Relocating agriculture could drastically reduce humanity’s ecological footprint

This paper optimizes global agricultural land use to reduce ecological footprints by relocating croplands and pastures, achieving significant reductions in carbon, biodiversity, and water footprints.

Adding Extra Knowledge in Scalable Learning of Sparse Differential Gaussian Graphical Models

This paper introduces KDiffNet, a method for estimating sparse differential Gaussian Graphical Models that integrates extra knowledge, achieving competitive performance and scalability.

Hierarchical Network Exploration using Gaussian MixtureModels

The paper introduces a framework using optimal mass transport to construct a network reduction hierarchy for interactive exploration and community detection, applied to gene regulatory networks and validated on biological datasets.

Neck Musculoskeletal Model Generation through Anthropometric Scaling

The paper develops a method to generate scaled musculoskeletal neck models using anthropometric data and optimization, showing accuracy in geometry and strength.

Optimal Mass Transport Kinetic Modeling for Head and Neck DCE-MRI: Initial Analysis

This study introduces an optimal mass transport model to analyze contrast agent flow in head and neck cancer patients, showing comparable results to traditional methods.

Optogenetic control of Wnt signaling for modeling early embryogenic patterning with human pluripotent stem cells

This study uses optogenetic control of Wnt signaling to induce mesendoderm differentiation and gastrulation-like morphogenesis in human pluripotent stem cells.

Personalized therapy design for liquid tumors via optimal control theory

This paper applies optimal control theory to design personalized cancer therapies, showing that individual pharmacokinetic differences significantly impact treatment outcomes.

Optimal control of acute myeloid leukaemia

This paper develops optimal chemotherapy strategies for AML by incorporating immune response into a stem cell model and applying optimal control theory.

Reducing false positives in tractography with microstructural and anatomical priors

The paper improves tractography by reducing false positives using anatomical priors and group-sparsity regularization in a convex optimization framework.

Enhanced flux prediction by integrating relative expression and relative metabolite abundance into thermodynamically consistent metabolic models

This paper introduces REMI, a method that integrates gene expression and metabolomic data into metabolic models to improve flux predictions and better reflect physiological states.

Data Distribution for Phylogenetic Inference with Site Repeats via Judicious Hypergraph Partitioning

The paper introduces HyperPhylo, a tool for efficient data distribution in phylogenetic inference with site repeats, showing improved performance over naive methods.

Best-compromise nutritional menus for childhood obesity

This paper develops a multiobjective mathematical model to create personalized nutritional menus for children to prevent obesity by minimizing glycemic load, cholesterol, and cost.

EM-LDDMM for 3D to 2D registration

The paper introduces an EM-LDDMM algorithm for registering 3D atlases to 2D sparse target sections, handling uncertainties through hidden variables and diffeomorphic mappings.

Cell Lineage and Communication Network Inference via Optimization for Single-Cell Transcriptomics

This paper introduces SoptSC, a method that integrates clustering, lineage inference, and communication network prediction in single-cell transcriptomics using a similarity matrix optimization framework.

Featherweight long read alignment using partitioned reference indexes

The paper reduces memory requirements for long read alignment on mobile devices by optimizing parameters and merging techniques, enabling human genome alignment with 2GB RAM without accuracy loss.

The number of active metabolic pathways is bounded by the number of cellular constraints at maximal metabolic rates

The paper shows that maximizing microbial growth rate limits the number of active metabolic pathways to the number of enzyme expression constraints, explaining simple metabolic behaviors through evolutionary optimization.

Holistic optimization of an RNA-seq workflow for multi-threaded environments

The paper optimizes an RNA-seq workflow for multi-threaded environments, achieving significant speed improvements by optimizing all steps, not just alignment.

Unification of optimal targeting methods in Transcranial Electrical Stimulation

This paper unifies different optimization methods for transcranial electrical stimulation by showing they are specific cases of a general optimization framework.

Learning to evoke complex motor outputs with spatiotemporal neurostimulation using a hierarchical and adaptive optimization algorithm.

This paper introduces a hierarchical and adaptive optimization algorithm to efficiently map spatiotemporal neurostimulation patterns to motor outputs in non-human primates, revealing nonlinear computations in M1.

Designing Distributed Cell Classifier Circuits using a Genetic Algorithm

This paper designs distributed cell classifiers using a genetic algorithm to improve accuracy and flexibility in cancer-type specific cell targeting.

A Multi-Scale Modelling Framework of the Whole Human Body Based on Multi-Objective Functions

This paper develops a multi-scale metabolic model of the human body with 3555 ODEs and 1826 reactions, solving 74 objectives to simulate metabolic phenotypes.

Optimizing the conservation of migratory species over their full annual cycle

This study evaluates land prioritization strategies for conserving migratory birds by comparing annual vs. weekly optimization and inclusion of human-dominated lands.

Precisely control mitochondria with light to manipulate cell fate decision

This paper develops an optogenetic method to control mitochondrial membrane potential and shows its effects on cell fate, finding that light-induced depolarization can induce apoptosis or cytoprotection depending on duration and intensity.

PLUG (Pruning of Local Unrealistic Geometries) removes restrictions on biophysical modeling for protein design

PLUG improves protein design by removing biophysical model restrictions through conformational pruning, achieving effectiveness comparable to DEE for larger designs.

Charting a tissue from single-cell transcriptomes

The paper introduces a method to reconstruct spatial positions of cells from single-cell transcriptomes without reference imaging data, leveraging expression space distances.