1,667 research outputs found
Control Engineering Approaches to Reverse Engineering Biomolecular NetworksHandbook of Statistical Systems Biology
No full textBates Letter, 1902
No full textF. L. Bates was an author on the Lincoln assassination and a lawyer. He believed Booth escaped the Garrett Farm barn. In the bulk of this letter Bates explains, at least to his satisfaction, that he has a tintype of a man he believes to be Booth, which can prove his belief about Booth's escape to others.As a young man in Granbury, Texas, Bates met local barkeep John St. Helen, who claimed to be John Wilkes Booth, long a fugitive following his murder of Abraham Lincoln. Bates believed St. Helen's story. Years later when another would-be Booth, David George, committed suicide in Oklahoma, Bates viewed the body and decided it was that of his old acquaintance St. Helen. Bates acquired the corpse and for years he and his heirs exhibited the mummified remains throughout the South. Bates promoted his contention in "Escape and Suicide of John Wilkes Booth," published in 1907, which included a purported confession
Implementing nonlinear feedback controllers using DNA strand displacement reactions
No full textWe show how an important class of nonlinear feedback controllers can be designed using idealized abstract chemical reactions and implemented via DNA strand displacement (DSD) reactions. Exploiting chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks, we show how a set of unimolecular and bimolecular reactions can be used to realize input-output dynamics that produce a nonlinear quasi sliding mode (QSM) feedback controller. The kinetics of the required chemical reactions can then be implemented as enzyme-free, enthalpy/entropy driven DNA reactions using a toehold mediated strand displacement mechanism via Watson-Crick base pairing and branch migration. We demonstrate that the closed loop response of the nonlinear QSM controller outperforms a traditional linear controller by facilitating much faster tracking response dynamics without introducing overshoots in the transient response. The resulting controller is highly modular and is less affected by retroactivity effects than standard linear designs
Biomolecular implementation of a quasi sliding mode feedback controller based on DNA strand displacement reactions
No full textA fundamental aim of synthetic biology is to achieve the capability to design and implement robust embedded biomolecular feedback control circuits. An approach to realize this objective is to use abstract chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks. Here, we employ this approach to facilitate the implementation of a class of nonlinear feedback controllers based on sliding mode control theory. We show how a set of two-step irreversible reactions with ultrasensitive response dynamics can provide a biomolecular implementation of a nonlinear quasi sliding mode (QSM) controller. We implement our controller in closed-loop with a prototype of a biological pathway and demonstrate that the nonlinear QSM controller outperforms a traditional linear controller by facilitating faster tracking response dynamics without introducing overshoots in the transient response
Biomolecular Implementation of a Quasi Sliding Mode Controller using an Ultrasensitive Cell Signalling Pathway
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Early Prediction of Non-Invasive Ventilation Outcome using the TabPFN Machine Learning Model: A Multi-Centre Validation Study
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Biomolecular implementation of a quasi sliding mode feedback controller based on DNA strand displacement reactions
No full textReverse-Engineering Biological Interaction Networks from Noisy Data using Regularized Least Squares and Instrumental Variables
No full textThe problem of reverse engineering the topology
of a biological network from noisy time–series measurements
is one of the most important challenges in the field of Systems
Biology. In this work, we develop a new inference approach
which combines the Regularized Least Squares (RLS) technique
with a technique to avoid the introduction of bias and nonconsistency
due to measurement noise in the estimation of the
parameters in the standard Least Squares (LS) formulation, the
Instrumental Variables (IV) method. We test our approach on a
set of nonlinear in silico networks and show that the combined
exploitation of RLS and IV methods improves the predictions
with respect to other standard approaches
Biomolecular Implementation of a Quasi Sliding Mode Controller using an Ultrasensitive Cell Signalling Pathway
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