optimal transport

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

This paper introduces ImageAEOT, a method combining autoencoders and optimal transport to infer single-cell trajectories from imaging data, validated on chromatin images of cancer cells and tissues.

RegKnock predicts gene knockout strategies for microbial strain optimization using a metabolic-regulatory integrated network and parallel genetic algorithm.

The paper investigates whether multi-objective MSA formulations improve phylogenetic tree estimation and finds they do, outperforming single-objective methods.

BicGO is a biclustering algorithm that accurately identifies complex biclusters in large datasets using global optimization, outperforming existing tools on both simulated and real data.

The paper introduces non-procedural methods for 3D genome reconstruction from Hi-C data, showing they can accurately model fission yeast genome structure.

This paper introduces a hierarchical optimization method for parameter estimation in ODE models using relative data, showing improved convergence and computational efficiency.

HapCHAT improves haplotype assembly by adapting error thresholds for higher coverage long reads, enhancing accuracy and reducing computational resources.

The paper optimizes timing and size of gene flow introduction to maximize genome survival in recipient populations, showing that action is better than inaction despite outbreeding depression.

This paper introduces BATISCAF, a repeat-aware scaffolder that outperforms existing tools on benchmark datasets.

AlphaMate optimizes selection, diversity maintenance, and mate allocation in breeding programs using multi-objective evolutionary algorithms, improving genetic gain efficiency in plants and animals.

This paper designs TMS coils that optimize the trade-off between depth, focality, and energy, achieving up to 55% smaller stimulated volume compared to existing designs.

The paper introduces an all-optical platform for high-throughput electrophysiology in human stem-cell-derived cardiomyocytes using optogenetic stimulation and optical imaging.

This paper introduces a method to reversibly control GPCR activity using photoswitchable ligands tethered via SNAP-tagged nanobodies.

The paper introduces PMFA, a method combining PCA and stoichiometric flux analysis for metabolic flux mode analysis, showing its versatility through experiments.

The paper improves the generation of virtual populations in QSP models by using alternative optimization algorithms and objective functions to reduce the number of required virtual patients while maintaining diversity.

This paper presents a computational framework for designing stochastic biocircuits with specified statistical properties using optimization and sensitivity analysis.

This paper introduces QSdpR, a correlation clustering method for viral quasispecies reconstruction, showing improved accuracy over existing methods on synthetic and real data.

Aether uses linear programming to optimally deploy cloud resources for genomics tasks, achieving cost savings and efficiency in metagenomic assembly.

This study develops ATI, a method to control biofilm formation in Pseudomonas aeruginosa by manipulating single-cell behaviors through optogenetics and tracking.

RetSynth identifies all optimal retrosynthesis pathways for target chemicals using dynamically constrained integer linear programming.

This paper introduces a genetic algorithm-based gene prediction method, GPGA, which improves efficiency by focusing on individual exons and demonstrates comparable performance on benchmark datasets and human chromosome 21 annotation.

The paper introduces a data-guided algorithm for cellular reprogramming using transcription factors, validated on human fibroblasts and showing potential for tissue regeneration and cancer cell reprogramming.

Optimal transport converts a 65,781-cell reprogramming time course into probabilistic fates and trajectories, exposing alternative cell fates and a gene, Obox6, that improves reprogramming efficiency.

This paper introduces CO-pRF, a convex optimization framework for pRF mapping that improves speed and reliability compared to traditional nonlinear methods.

This study aligns two zebrafish brain atlases using symmetric diffeomorphic normalization, improving registration precision and preserving morphology.

This review discusses mathematical and computational models addressing challenges in cancer immunotherapy, including tumor classification, treatment scheduling, and combination therapy design.

This paper introduces an optogenetic tool, SxIP-iLID, to control microtubule dynamics by cross-linking MT plus ends with F-actin, revealing effects on MT growth and lamellar exclusion zones.

The paper shows overtraining in maximum likelihood species tree reconstruction leads to topologically incorrect trees, and identifies likelihood curve shape as a guide for optimal stopping.

This study introduces BLInCR, a tool for real-time observation of light-controlled transcription in living cells, showing rapid RNA production and biphasic activation kinetics.