Publications
2023
Motor processivity and speed determine structure and dynamics of microtubule-motor assemblies
Rachel A Banks, Vahe Galstyan, Heun Jin Lee, Soichi Hirokawa, Athena Ierokomos, Tyler D Ross, Zev Bryant, Matt Thomson, Rob Phillips
2023, eLife 12:e79402
2022
Stem cell-derived synthetic embryos self-assemble by exploiting cadherin codes and cortical tension
Connectedness of loss landscapes via the lens of Morse theory
Danil Akhtiamov and Matt Thomson
NeurIPS Symmetry and Geometry in Neural Representations, 2022
Generating counterfactual explanations of tumor spatial proteomes to discover effective, combinatorial therapies that enhance cancer immunotherapy
Zitong Jerry Wang and Matt Thomson
NeurIPS AI for Science, 2022
Neural networks learn an environment’s geometry in latent space by performing predictive coding on visual scenes
James Gornet and Matt Thomson
NeurIPS Information-theoretic Principles in Cognitive Science, 2022
Control of spatio-temporal patterning via cell density in a multicellular synthetic gene circuit
Mapping hormone-regulated cell-cell interaction networks in the human breast at single-cell resolution
Localization of signaling receptors maximizes cellular information acquisition in spatially structured natural environments
Minimal gene set discovery in single-cell mRNA-seq datasets with ActiveSVM
Xiaoqiao Chen, Sisi Chen & Matt Thomson
Nature Computational Science, 2022
Reinforcement learning reveals fundamental limits on the mixing of active particles
Dominik Schildknecht, Anastasia N Popova, Jack Stellwagen & Matthew Thomson
Soft Matter, 2022
Linear Transformations in Autoencoder Latent Space Predict Time Translations in Active Matter System
Enrique Amaya, Shahriar Shadkhoo, Dominik Schildknecht & Matt Thomson
NeurIPS AI for Science, 2021
A DNA repair pathway can regulate transcriptional noise to promote cell fate transitions
Engineering flexible machine learning systems by traversing functionally invariant paths in weight space
Dynamic Flow Control Through Active Matter Programming Language
Fan Yang, Shichen Liu, Heun Jin Lee, Matt Thomson
arXiv preprint, 2022
Persistent fluid flows defined by active matter boundaries
Deep parallel characterization of AAV tropism and AAV-mediated transcriptional changes via single-cell RNA sequencing
CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq
Reconstructing aspects of human embryogenesis with pluripotent stem cells
Deep parallel characterization of AAV tropism and AAV-mediated transcriptional changes via single-cell RNA sequencing
Phenomenological model of motility by spatiotemporal modulation of active interactions
Dominik Schildknecht, Matt Thomson
New Journal of Physics, 2021
Active feature selection discovers minimal gene-sets for classifying cell-types and disease states in single-cell mRNA-seq data
Xiaoqiao Chen, Sisi Chen, and Matt Thomson
arXiv preprint, 2021
Solving hybrid machine learning tasks by traversing weight space geodesics
Reinforcement Learning reveals fundamental limits on the mixing of active particles
Dominik Schildknecht, Anastasia N. Popova, Jack Stellwagen, and Matt Thomson
arXiv preprint, 2021
Sparsifying Networks by Traversing Geodesics
Developmental clock and mechanism of de novo polarization of the mouse embryo
Single cell profiling of capillary blood enables out of clinic human immunity studies
Tatyana Dobreva, David Brown, Jong Hwee Park, and Matt Thomson
Scientific Reports, 2020
Dissecting heterogeneous cell populations across drug and disease conditions with PopAlign
Programming Boundary Deformation Patterns in Active Networks
Persistent fluid flows defined by active matter boundaries
Self-organization of multi-layer spiking neural networks
Guruprasad Raghavan, Cong Lin, Matt Thomson
arXiv preprint, 2020
Geometric algorithms for predicting resilience and recovering damage in neural networks
Guruprasad Raghavan, Jiayi Li, Matt Thomson
arXiv preprint, 2020
Designing signaling environments to steer transcriptional diversity in neural progenitor cell populations
Jong H. Park, Tiffany Tsou, Paul Rivaud, Matt Thomson and Sisi Chen
bioRxiv, 2020
Highly Multiplexed Single-Cell RNA-seq for Defining Cell Population and Transcriptional Spaces
Controlling Organization and Forces in Active Matter Through Optically-Defined Boundaries
Active Learning of Spin Network Models
Jialong Jiang, David A. Sivak and Matt Thomson
arXiv preprint, 2019
Neural networks grown and self-organized by noise
Diffusion as a Ruler: Modeling Kinesin Diffusion as a Lenth Sensor for Intraflagellar Transport
Adult Neurogenesis Is Sustained by Symmetric Self-Renewal and Differentiation
Diffusion as a Ruler: Modeling Kinesin Diffusion as a Length Sensor for Intraflagellar Transport
Diffusion as a ruler: Modeling kinesin diffusion as a length sensor for intraflagellar transport
Transient Thresholding: A Mechanism Enabling Noncooperative Transcriptional Circuitry to Form a Switch
SOX2O-GlcNAcylation alters its protein-protein interactions and genomic occupancy to modulate gene expression in pluripotent cells.
Low Dimensionality in Gene Expression Data Enables the Accurate Extraction of Transcriptional Programs from Shallow Sequencing
Engineering Customized Cell Sensing and Response Behaviors Using Synthetic Notch Receptors
Signaling Boundary Conditions Drive Self-Organization of Human “Gastruloids”.
Matthew Thomson
Developmental Cell, 39 (3). pp. 279-280. ISSN 1534-5807, 2016