Michael P Brenner

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 26

Top Topics

Molecular Dynamics Simulations

Machine Learning

Gene Expression

Top Venues

Proceedings of the National Academy of Sciences of the United States of America

Nature communications

Science advances

This page only lists publications with an associated author ORCID identifier.

Publications

Ella M King, Chrisy Xiyu Du, Qian-Ze Zhu, Samuel S Schoenholz, Michael P Brenner
Programming patchy particles for materials assembly design. Proceedings of the National Academy of Sciences of the United States of America 121 (27) (2024)
Jacob Page, Peter Norgaard, Michael P Brenner, Rich R Kerswell
Recurrent flow patterns as a basis for two-dimensional turbulence: Predicting statistics from structures. Proceedings of the National Academy of Sciences of the United States of America 121 (23) (2024)
Jacob Page, Peter Norgaard, Michael P Brenner, Rich R Kerswell
Recurrent flow patterns as a basis for two-dimensional turbulence: Predicting statistics from structures. Proceedings of the National Academy of Sciences of the United States of America 121 (23) (2024)
Jacob Page, Peter Norgaard, Michael P Brenner, Rich R Kerswell
Recurrent flow patterns as a basis for two-dimensional turbulence: Predicting statistics from structures. Proceedings of the National Academy of Sciences of the United States of America 121 (23) (2024)
Ella M King, Chrisy Xiyu Du, Qian-Ze Zhu, Samuel S Schoenholz, Michael P Brenner
Programming patchy particles for materials assembly design. Proceedings of the National Academy of Sciences of the United States of America 121 (27) (2024)
Ella M King, Chrisy Xiyu Du, Qian-Ze Zhu, Samuel S Schoenholz, Michael P Brenner
Programming patchy particles for materials assembly design. Proceedings of the National Academy of Sciences of the United States of America 121 (27) (2024)
Ofer Kimchi, Ella M King, Michael P Brenner
Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition. Nature communications 14 (1) (2023)
Ofer Kimchi, Ella M King, Michael P Brenner
Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition. Nature communications 14 (1) (2023)
Soeren Brandt, Ida Pavlichenko, Anna V Shneidman, Haritosh Patel, Austin Tripp, Timothy S B Wong, Sean Lazaro, Ethan Thompson, Aubrey Maltz, Thomas Storwick, Holden Beggs, Katalin Szendrei-Temesi, Bettina V Lotsch, C Nadir Kaplan, Claas W Visser, Michael P Brenner, Venkatesh N Murthy, Joanna Aizenberg
Nonequilibrium sensing of volatile compounds using active and passive analyte delivery. Proceedings of the National Academy of Sciences of the United States of America 120 (31) (2023)
Ofer Kimchi, Ella M King, Michael P Brenner
Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition. Nature communications 14 (1) (2023)
Agnese I Curatolo, Ofer Kimchi, Carl P Goodrich, Ryan K Krueger, Michael P Brenner
A computational toolbox for the assembly yield of complex and heterogeneous structures. Nature communications 14 (1) (2023)
Ofer Kimchi, Ella M King, Michael P Brenner
Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition. Nature communications 14 (1) (2023)
Agnese I Curatolo, Ofer Kimchi, Carl P Goodrich, Ryan K Krueger, Michael P Brenner
A computational toolbox for the assembly yield of complex and heterogeneous structures. Nature communications 14 (1) (2023)
Agnese I Curatolo, Ofer Kimchi, Carl P Goodrich, Ryan K Krueger, Michael P Brenner
A computational toolbox for the assembly yield of complex and heterogeneous structures. Nature communications 14 (1) (2023)
Ofer Kimchi, Ella M King, Michael P Brenner
Uncovering the mechanism for aggregation in repeat expanded RNA reveals a reentrant transition. Nature communications 14 (1) (2023)
Cheng Zeng, Maya Winters Faaborg, Ahmed Sherif, Martin J Falk, Rozhin Hajian, Ming Xiao, Kara Hartig, Yohai Bar-Sinai, Michael P Brenner, Vinothan N Manoharan
3D-printed machines that manipulate microscopic objects using capillary forces. Nature 611 (7934) (2022)
Mor Nitzan, Michael P Brenner
Revealing lineage-related signals in single-cell gene expression using random matrix theory. Proceedings of the National Academy of Sciences of the United States of America 118 (11) (2021)
Yipei Guo, Mor Nitzan, Michael P Brenner
Programming cell growth into different cluster shapes using diffusible signals. PLoS computational biology 17 (11) (2021)
Krishna Shrinivas, Michael P Brenner
Phase separation in fluids with many interacting components. Proceedings of the National Academy of Sciences of the United States of America 118 (45) (2021)
Dmitrii Kochkov, Jamie A Smith, Ayya Alieva, Qing Wang, Michael P Brenner, Stephan Hoyer
Machine learning-accelerated computational fluid dynamics. Proceedings of the National Academy of Sciences of the United States of America 118 (21) (2021)
Carl P Goodrich, Ella M King, Samuel S Schoenholz, Ekin D Cubuk, Michael P Brenner
Designing self-assembling kinetics with differentiable statistical physics models. Proceedings of the National Academy of Sciences of the United States of America 118 (10) (2021)
Ling Li, Carl Goodrich, Haizhao Yang, Katherine R Phillips, Zian Jia, Hongshun Chen, Lifeng Wang, Jinjin Zhong, Anhua Liu, Jianfeng Lu, Jianwei Shuai, Michael P Brenner, Frans Spaepen, Joanna Aizenberg
Microscopic origins of the crystallographically preferred growth in evaporation-induced colloidal crystals. Proceedings of the National Academy of Sciences of the United States of America 118 (32) (2021)
Ofer Kimchi, Carl P Goodrich, Alexis Courbet, Agnese I Curatolo, Nicholas B Woodall, Julien S Baker, Michael P Brenner
Self-assembly-based posttranslational protein oscillators. Science advances 6 (51) (2020)
Ran Niu, Chrisy Xiyu Du, Edward Esposito, Jakin Ng, Michael P Brenner, Paul L McEuen, Itai Cohen
Magnetic handshake materials as a scale-invariant platform for programmed self-assembly. Proceedings of the National Academy of Sciences of the United States of America 116 (49) (2019)
Kevin McCloskey, Ankur Taly, Federico Monti, Michael P Brenner, Lucy J Colwell
Using attribution to decode binding mechanism in neural network models for chemistry. Proceedings of the National Academy of Sciences of the United States of America 116 (24) (2019)
Yohai Bar-Sinai, Stephan Hoyer, Jason Hickey, Michael P Brenner
Learning data-driven discretizations for partial differential equations. Proceedings of the National Academy of Sciences of the United States of America 116 (31) (2019)