Massive computational acceleration by using neural networks to emulate mechanism-based biological models
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Massive computational acceleration by using neural networks to emulate mechanism-based biological models
Authors
Keywords
-
Journal
Nature Communications
Volume 10, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-09-25
DOI
10.1038/s41467-019-12342-y
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Synthetic Pattern Formation
- (2019) Nan Luo et al. BIOCHEMISTRY
- Stochastic Turing patterns in a synthetic bacterial population
- (2018) David Karig et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Computational Re-design of Synthetic Genetic Oscillators for Independent Amplitude and Frequency Modulation
- (2018) Marios Tomazou et al. Cell Systems
- Biophysical experiments and biomolecular simulations: A perfect match?
- (2018) Sandro Bottaro et al. SCIENCE
- Deep neural networks for accurate predictions of crystal stability
- (2018) Weike Ye et al. Nature Communications
- Agent-Based Modeling Reveals Possible Mechanisms for Observed Aggregation Cell Behaviors
- (2018) Zhaoyang Zhang et al. BIOPHYSICAL JOURNAL
- Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- (2018) M. Raissi et al. JOURNAL OF COMPUTATIONAL PHYSICS
- ANI-1: an extensible neural network potential with DFT accuracy at force field computational cost
- (2017) J. S. Smith et al. Chemical Science
- Collective Space-Sensing Coordinates Pattern Scaling in Engineered Bacteria
- (2016) Yangxiaolu Cao et al. CELL
- A physiologically based kinetic model for elucidating the in vivo distribution of administered mesenchymal stem cells
- (2016) Haolu Wang et al. Scientific Reports
- Translating slow-binding inhibition kinetics into cellular and in vivo effects
- (2015) Grant K Walkup et al. Nature Chemical Biology
- Quantitative and logic modelling of molecular and gene networks
- (2015) Nicolas Le Novère NATURE REVIEWS GENETICS
- A constrained integration (CINT) approach to solving partial differential equations using artificial neural networks
- (2015) Keith Rudd et al. NEUROCOMPUTING
- Synchronization of Degrade-and-Fire Oscillations via a Common Activator
- (2014) William Mather et al. PHYSICAL REVIEW LETTERS
- Temporal control of self-organized pattern formation without morphogen gradients in bacteria
- (2013) S. Payne et al. Molecular Systems Biology
- Systematic identification of proteins that elicit drug side effects
- (2013) M. Kuhn et al. Molecular Systems Biology
- Simulating Robots Without Conventional Physics: A Neural Network Approach
- (2012) C. J. Pretorius et al. JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
- Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning
- (2012) Matthias Rupp et al. PHYSICAL REVIEW LETTERS
- Quantitative mathematical modeling of PSA dynamics of prostate cancer patients treated with intermittent androgen suppression
- (2012) Yoshito Hirata et al. Journal of Molecular Cell Biology
- Viral-Mediated Noisy Gene Expression Reveals Biphasic E2f1 Response to MYC
- (2011) Jeffrey V. Wong et al. MOLECULAR CELL
- A Decade of Systems Biology
- (2010) Han-Yu Chuang et al. Annual Review of Cell and Developmental Biology
- Population Modeling of Influenza A/H1N1 Virus Kinetics and Symptom Dynamics
- (2010) L. Canini et al. JOURNAL OF VIROLOGY
- A synchronized quorum of genetic clocks
- (2010) Tal Danino et al. NATURE
- Reaction-Diffusion Model as a Framework for Understanding Biological Pattern Formation
- (2010) S. Kondo et al. SCIENCE
- Stochastic E2F Activation and Reconciliation of Phenomenological Cell-Cycle Models
- (2010) Tae J. Lee et al. PLOS BIOLOGY
- Defining Network Topologies that Can Achieve Biochemical Adaptation
- (2009) Wenzhe Ma et al. CELL
- A tunable synthetic mammalian oscillator
- (2009) Marcel Tigges et al. NATURE
- Diversity-based, model-guided construction of synthetic gene networks with predicted functions
- (2009) Tom Ellis et al. NATURE BIOTECHNOLOGY
- Emergent bistability by a growth-modulating positive feedback circuit
- (2009) Cheemeng Tan et al. Nature Chemical Biology
- A fast, robust and tunable synthetic gene oscillator
- (2008) Jesse Stricker et al. NATURE
- A bistable Rb–E2F switch underlies the restriction point
- (2008) Guang Yao et al. NATURE CELL BIOLOGY
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now