Inference and Stochastic Processes in Biophysics
FOCUS · A47
Presentations
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Quantifying the invisible: Bayesian approaches in fluorescence microscopy
Invited
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Presenters
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Ioannis Sgouralis
Physics, Arizona State Univ, Center for Biological Physics, Arizona State University
Authors
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Ioannis Sgouralis
Physics, Arizona State Univ, Center for Biological Physics, Arizona State University
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Biophysical inference mechanisms face a trade-off between external and internal noise resistance
ORAL
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Presenters
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Weerapat Pittayakanchit
University of Chicago
Authors
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Weerapat Pittayakanchit
University of Chicago
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Zhiyue Lu
University of Chicago
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Justin Chew
University of Chicago
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Michael Rust
University of Chicago
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Arvind Murugan
Physics, University of Chicago, University of Chicago, James Franck Institute, University of Chicago
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Inference of mechanical stresses within the actively migrating cell sheet
ORAL
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Presenters
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Yoav Green
Harvard University
Authors
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Yoav Green
Harvard University
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James Butler
Harvard University
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Jeffery Fredberg
Harvard University
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Inference of Network Connectivity from Dynamics
ORAL
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Presenters
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Emily SC Ching
Department of Physics, The Chinese University of Hong Kong
Authors
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Emily SC Ching
Department of Physics, The Chinese University of Hong Kong
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Adaptive trust in internal models alleviates trade-offs in biophysical inference of the environment
ORAL
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Presenters
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Arvind Murugan
Physics, University of Chicago, University of Chicago, James Franck Institute, University of Chicago
Authors
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Amir Bitran
Harvard University
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Ofer Kimchi
Biophysics, Harvard University, Harvard University
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Mirna Kramar
Max Planck Institute for Dynamics and Self-Organization
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Amanda Parker
University of California, Davis
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Ching-Hao Wang
Physics, Boston Univ, Boston University
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Gopal Pattanayak
University of Chicago
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Michael Rust
University of Chicago
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Arvind Murugan
Physics, University of Chicago, University of Chicago, James Franck Institute, University of Chicago
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Bayesian nonparametrics for biophysics
ORAL
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Presenters
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Steve Presse
Univ of California - San Francisco, Physics and School of Molecular Sciences, Arizona State University
Authors
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Steve Presse
Univ of California - San Francisco, Physics and School of Molecular Sciences, Arizona State University
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Progress in estimation of mutual information for real-valued data
ORAL
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Presenters
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Ilya Nemenman
Emory Univ, Emory University, Department of Physics, Department of Biology, Emory University
Authors
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Caroline Holmes
Princeton Univ
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Ilya Nemenman
Emory Univ, Emory University, Department of Physics, Department of Biology, Emory University
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The Limitations of Model-Based Experimental Design and Parameter Estimation in Sloppy Systems
ORAL
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Presenters
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Mark Transtrum
Physics & Astronomy, Brigham Young University
Authors
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Mark Transtrum
Physics & Astronomy, Brigham Young University
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Data-Driven Inference for Jump-Diffusion Models of Neuroscientific Data
ORAL
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Presenters
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Alexandre Melanson
Physics, University of Ottawa
Authors
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Alexandre Melanson
Physics, University of Ottawa
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Andre Longtin
Physics, University of Ottawa
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Multilevel Bayesian Analysis of Biophysical Data in the Presence of Model Inadequacy and Measurement Error
ORAL
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Presenters
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Amir Shahmoradi
Univ of Texas, Austin
Authors
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Amir Shahmoradi
Univ of Texas, Austin
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Rational Ignorance: Simpler Models Learn More Information from Finite Data
ORAL
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Presenters
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Henry Mattingly
Molecular, Cellular, and Developmental Biology, Yale University
Authors
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Henry Mattingly
Molecular, Cellular, and Developmental Biology, Yale University
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Mark Transtrum
Physics and Astronomy, Brigham Young Univ - Provo, Department of Physics and Astronomy, Brigham Young University
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Michael Abbott
Institute of Physics, Jagiellonian University
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Benjamin Machta
Physics, Yale University, Department of Physics and Systems Biology Institute, Yale University
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Inference of Transition Rates in a Birth-Death Chain from Conditional Exit Times
ORAL
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Presenters
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Pak-Wing Fok
Mathematical Sciences, University of Delaware
Authors
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Pak-Wing Fok
Mathematical Sciences, University of Delaware
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Density of isolated particles and the hydrodynamic limit of generalized TASEP models: Application to mRNA translation rate inference
ORAL
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Presenters
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Khanh Dao Duc
Computer Science, UC Berkeley
Authors
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Khanh Dao Duc
Computer Science, UC Berkeley
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Dan Erdmann-Pham
Mathematics, UC Berkeley
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Yun Song
Computer Science and Statistics, UC Berkeley
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