optimal transport

Informed, scalable and unified transport couplings for single-cell alignment and downstream inference with scBIOT

scBIOT introduces a biologically informed optimal transport framework for single-cell alignment, enabling scalable analysis and downstream biological inference across multiple tasks.

The membrane transition strongly enhances biopolymer condensation through prewetting

The paper shows that membrane prewetting enhances biopolymer condensation by lipid composition, observed in simulations, reconstitution, and cells.

Expert-guided multi-objective optimization: an efficient strategy for parameter estimation of biological systems with limited data.

This paper introduces a hybrid calibration framework that integrates expert knowledge into multi-objective optimization for biological model parameter estimation, showing improved biological relevance and reduced overfitting.

Risk-averse optimization of genetic circuits under uncertainty

This paper develops a risk-averse optimization framework combining Bayesian inference and Thompson sampling to design robust genetic circuits despite model inaccuracies and parameter uncertainty.

Optimisation of Weighted Ensembles of Genomic Prediction Models in Maize

This study evaluates three weight optimisation approaches for genomic prediction ensembles in maize, finding that weighted models improve prediction performance when weights differ from equal weights, but no single method clearly outperforms others.

Conditional Success of Adaptive Therapy: The Role of Treatment-Holiday Thresholds and Non-Existence of Optimal Strategies Revealed by Mathematical Modelling and Optimal Control

This paper uses mathematical modeling to show adaptive therapy's success depends on treatment thresholds and competitive interactions, with no optimal strategy due to impractical infinite treatment holidays.

GROTIA: An Interpretable Graph-Regularized Optimal TransportFramework for Diagonal Single-Cell IntegrativeAnalysis

GROTIA aligns multi-omics single-cell datasets using optimal transport and graph regularization, identifying key biological markers and enabling novel subpopulation discovery.

Planning and scheduling biological experiments across multiple liquid handling robots

The paper presents an optimization framework for coordinating multiple liquid handling robots to plan and schedule biological experiments efficiently.

PocketX: Preference Alignment for Protein Pockets Design through Group Relative Policy Optimization

PocketX uses reinforcement learning to align protein pocket design with biophysical properties, outperforming existing methods on binding energy and evolutionary plausibility.

Improving Cryo-EM Optimization Robustness with an Optimal Transport Loss Function for Noisy Images

This paper introduces a Sliced Wasserstein loss function to improve optimization robustness in cryo-EM, showing it outperforms MSE in handling noisy data and conformational heterogeneity.

Optogenetic Proximity Labeling Maps Spatially Resolved Mitochondrial Surface Proteomes and a Locally Regulated Ribosome Pool

The paper introduces optogenetic proximity labeling to map mitochondrial surface proteomes and ribosome pools, revealing Miro1's role in spatially organizing mitochondrial protein biogenesis.

Optimal feedback solutions recapitulate key features of motorcortical population dynamics

This paper develops a method to model neural population dynamics as optimal feedback solutions and shows they match recorded motorcortical responses.

From features to slice: parameter-cloud modeling of spatial transcriptomics for simulation and 3D interpolatory augmentation

FEAST generates synthetic spatial transcriptomics data with tunable spatial and transcriptional variation for benchmarking and 3D reconstruction.

Activation of hypothalamic-pontine-spinal pathway promotes locomotor initiation and functional recovery after spinal cord injury in mice

This study identifies a hypothalamic-pontine-spinal pathway that promotes locomotion and functional recovery after spinal cord injury in mice through optogenetic manipulation and deep brain stimulation.

SCOT+: A Comprehensive Software Suite for Single-Cell alignment Using Optimal Transport

SCOT+ aligns single-cell multi-omics data across datasets using optimal transport without requiring correspondence, improving downstream analysis accuracy.

Dynamic optimization of chemo-immunotherapy sequencing reveals phenotype-dependent regimens across tumor immune microenvironments

This paper develops a dynamic optimization framework to design chemo-immunotherapy regimens tailored to tumor immune microenvironment phenotypes.

MIMEco: Multi-objective metabolic modeling to predict and explain pairwise interactions

MIMEco predicts pairwise microbial interactions using multi-objective metabolic modeling without requiring abundance data, validated by replicating experimental results with Escherichia coli.

USHER: Guiding Foundation Model Representations through Distribution Shifts

USHER corrects out-of-distribution biases in foundation models by transforming embeddings to a reference space, improving cross-platform integration and downstream tasks.

sc4D: spatio-temporal single-cell transcriptomics analysis through embedded optimal transport identifies joint glial response to Alzheimer's disease pathology

sc4D integrates optimal transport with autoencoder embeddings to analyze spatio-temporal single-cell transcriptomics data, revealing glial responses to Alzheimer's disease pathology and predicting therapeutic interventions.

Using AI-MIDD for Mechanistic Erythropoietin Modeling: A Digital-Twin Framework for Optimizing ESA Therapies

The paper develops an AI-MIDD-QSP digital-twin framework to optimize ESA therapies by integrating mechanistic models of erythropoiesis and identifying dose-sparing strategies.

CelLink: integrating single-cell multi-omics data with weak feature linkage and imbalanced cell populations

CelLink integrates single-cell multi-omics data by addressing weak feature linkage and imbalanced cell populations, outperforming existing methods in imputation accuracy and cell subtype annotation.

LMI4Boltz: Optimising VRAM utilisation to predict large macromolecular complexes with consumer grade hardware

LMI4Boltz optimizes VRAM usage to predict large macromolecular complexes on consumer-grade hardware without sacrificing accuracy.

Quantum Deep Learning Pipeline for Next Generation Network Biology

The paper uses quantum optimization to identify biologically relevant modules in latent representations of omics data from human tissues.

Modulating inter-mitochondrial contacts to increase membrane potential for mitigating blue light damage

This paper introduces an optogenetic system to modulate mitochondrial membrane potential by forming inter-mitochondrial contacts, showing it mitigates blue light damage in retinal cells and C. elegans.

Design principles underlying nearly-homeostatic biological networks

The paper identifies two optimization approaches for designing near-homeostasis systems and introduces inverse homeostasis plots to uncover novel mechanisms.

Computational design and evaluation of optimal bait sets for scalable proximity proteomics

The paper develops GENBAIT, a genetic algorithm-based tool to optimize bait selection for BioID experiments, reducing bait numbers while maintaining dataset coverage and structure.

FlashRNA: An Efficient Model for Regulatory Genomics

FlashRNA improves computational efficiency for genomic sequence-to-function models while maintaining or enhancing predictive performance across multiple tasks.

Automated muscle path calibration with gradient-specified optimization based on moment arm

This paper introduces a gradient-specified optimization method to calibrate muscle paths based on desired moment arms, achieving fast and accurate replication of muscle paths from a shoulder-arm model.

Optogenetic construction of de novo integrin-adhesion complexes reveals role for biocondensation in adhesion nucleation

This paper uses optogenetics to test how talin's activity and phase states influence integrin-adhesion complex (IAC) nucleation and stabilization, finding that biocondensation enables adhesion formation even without extracellular matrix.

Optimal transport modeling uncovers spatial domain dynamics in spatiotemporal transcriptomics studies

SpaDOT identifies spatial domains and their temporal dynamics in spatiotemporal transcriptomics data, revealing key developmental processes like valvulogenesis.