LIVIVO - Search results -

Search results

Result 1 - 10 of total 32

Search options

Article ; Online: Design and Simulation of a Multilayer Chemical Neural Network That Learns via Backpropagation.

Lakin, Matthew R

2023 Volume 29, Issue 3, Page(s) 308–335

Abstract: The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning ... ...

Abstract	The design and implementation of adaptive chemical reaction networks, capable of adjusting their behavior over time in response to experience, is a key goal for the fields of molecular computing and DNA nanotechnology. Mainstream machine learning research offers powerful tools for implementing learning behavior that could one day be realized in a wet chemistry system. Here we develop an abstract chemical reaction network model that implements the backpropagation learning algorithm for a feedforward neural network whose nodes employ the nonlinear "leaky rectified linear unit" transfer function. Our network directly implements the mathematics behind this well-studied learning algorithm, and we demonstrate its capabilities by training the system to learn a linearly inseparable decision surface, specifically, the XOR logic function. We show that this simulation quantitatively follows the definition of the underlying algorithm. To implement this system, we also report ProBioSim, a simulator that enables arbitrary training protocols for simulated chemical reaction networks to be straightforwardly defined using constructs from the host programming language. This work thus provides new insight into the capabilities of learning chemical reaction networks and also develops new computational tools to simulate their behavior, which could be applied in the design and implementations of adaptive artificial life.
MeSH term(s)	Neural Networks, Computer ; Computer Simulation ; Algorithms ; Machine Learning ; DNA
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2023-05-04
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2024100-8
ISSN	1530-9185 ; 1064-5462
ISSN (online)	1530-9185
ISSN	1064-5462
DOI	10.1162/artl_a_00405
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article ; Online: A geometric framework for reaction enumeration in computational nucleic acid devices.

Kumar, Sarika / Lakin, Matthew R

Journal of the Royal Society, Interface

2023 Volume 20, Issue 208, Page(s) 20230259

Abstract: Cascades of DNA strand displacement reactions enable the design of potentially large circuits with complex behaviour. Computational modelling of such systems is desirable to enable rapid design and analysis. In previous work, the expressive power of ... ...

Abstract	Cascades of DNA strand displacement reactions enable the design of potentially large circuits with complex behaviour. Computational modelling of such systems is desirable to enable rapid design and analysis. In previous work, the expressive power of graph theory was used to enumerate reactions implementing strand displacement across a wide range of complex structures. However, coping with the rich variety of possible graph-based structures required enumeration rules with complicated side-conditions. This paper presents an alternative approach to tackle the problem of enumerating reactions at domain level involving complex structures by integrating with a geometric constraint solving algorithm. The rule sets from previous work are simplified by replacing side-conditions with a general check on the geometric plausibility of structures generated by the enumeration algorithm. This produces a highly general geometric framework for reaction enumeration. Here, we instantiate this framework to solve geometric constraints by a structure sampling approach in which we randomly generate sets of coordinates and check whether they satisfy all the constraints. We demonstrate this system by applying it to examples from the literature where molecular geometry plays an important role, including DNA hairpin and remote toehold reactions. This work therefore enables integration of reaction enumeration and structural modelling.
MeSH term(s)	Nucleic Acids ; DNA/chemistry ; Mathematics ; Algorithms
Chemical Substances	Nucleic Acids ; DNA (9007-49-2)
Language	English
Publishing date	2023-11-15
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2156283-0
ISSN	1742-5662 ; 1742-5689
ISSN (online)	1742-5662
ISSN	1742-5689
DOI	10.1098/rsif.2023.0259
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Supervised Learning in a Multilayer, Nonlinear Chemical Neural Network.

Arredondo, David / Lakin, Matthew R

IEEE transactions on neural networks and learning systems

2023 Volume 34, Issue 10, Page(s) 7734–7745

Abstract: The development of programmable or trainable molecular circuits is an important goal in the field of molecular programming. Multilayer, nonlinear, artificial neural networks are a powerful framework for implementing such functionality in a molecular ... ...

Abstract	The development of programmable or trainable molecular circuits is an important goal in the field of molecular programming. Multilayer, nonlinear, artificial neural networks are a powerful framework for implementing such functionality in a molecular system, as they are provably universal function approximators. Here, we present a design for multilayer chemical neural networks with a nonlinear hyperbolic tangent transfer function. We use a weight perturbation algorithm to train the neural network which uses a simple construction to directly approximate the loss derivatives required for training. We demonstrate the training of this system to learn all 16 two-input binary functions from a common starting point. This work thus introduces new capabilities in the field of adaptive and trainable chemical reaction network (CRN) design. It also opens the door to potential future experimental implementations, including DNA strand displacement reactions.
Language	English
Publishing date	2023-10-05
Publishing country	United States
Document type	Journal Article
ISSN	2162-2388
ISSN (online)	2162-2388
DOI	10.1109/TNNLS.2022.3146057
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Heterochiral modifications enhance robustness and function of DNA in living human cells.

Mallette, Tracy L / Lidke, Diane S / Lakin, Matthew R

Chembiochem : a European journal of chemical biology

2024 Volume 25, Issue 5, Page(s) e202300755

Abstract: Oligonucleotide therapeutics are becoming increasingly important as more are approved by the FDA, both for treatment and vaccination. Similarly, dynamic DNA nanotechnology is a promising technique that can be used to sense exogenous input molecules or ... ...

Abstract	Oligonucleotide therapeutics are becoming increasingly important as more are approved by the FDA, both for treatment and vaccination. Similarly, dynamic DNA nanotechnology is a promising technique that can be used to sense exogenous input molecules or endogenous biomarkers and integrate the results of multiple sensing reactions in situ via a programmed cascade of reactions. The combination of these two technologies could be highly impactful in biomedicine by enabling smart oligonucleotide therapeutics that can autonomously sense and respond to a disease state. A particular challenge, however, is the limited lifetime of standard nucleic acid components in living cells and organisms due to degradation by endogenous nucleases. In this work, we address this challenge by incorporating mirror-image, ʟ-DNA nucleotides to produce heterochiral "gapmers". We use dynamic DNA nanotechnology to show that these modifications keep the oligonucleotide intact in living human cells for longer than an unmodified strand. To this end, we used a sequential transfection protocol for delivering multiple nucleic acids into living human cells while providing enhanced confidence that subsequent interactions are actually occurring within the cells. Taken together, this work advances the state of the art of ʟ-nucleic acid protection of oligonucleotides and DNA circuitry for applications in vivo.
MeSH term(s)	Humans ; DNA ; Nucleic Acids ; Oligonucleotides ; Endonucleases ; Nanotechnology
Chemical Substances	DNA (9007-49-2) ; Nucleic Acids ; Oligonucleotides ; Endonucleases (EC 3.1.-)
Language	English
Publishing date	2024-02-12
Publishing country	Germany
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	2020469-3
ISSN	1439-7633 ; 1439-4227
ISSN (online)	1439-7633
ISSN	1439-4227
DOI	10.1002/cbic.202300755
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Operant conditioning of stochastic chemical reaction networks.

Arredondo, David / Lakin, Matthew R

PLoS computational biology

2022 Volume 18, Issue 11, Page(s) e1010676

Abstract: Adapting one's behavior to environmental conditions and past experience is a key trait of living systems. In the biological world, there is evidence for adaptive behaviors such as learning even in naturally occurring, non-neural, single-celled organisms. ...

Abstract	Adapting one's behavior to environmental conditions and past experience is a key trait of living systems. In the biological world, there is evidence for adaptive behaviors such as learning even in naturally occurring, non-neural, single-celled organisms. In the bioengineered world, advances in synthetic cell engineering and biorobotics have created the possibility of implementing lifelike systems engineered from the bottom up. This will require the development of programmable control circuitry for such biomimetic systems that is capable of realizing such non-trivial and adaptive behavior, including modification of subsequent behavior in response to environmental feedback. To this end, we report the design of novel stochastic chemical reaction networks capable of probabilistic decision-making in response to stimuli. We show that a simple chemical reaction network motif can be tuned to produce arbitrary decision probabilities when choosing between two or more responses to a stimulus signal. We further show that simple feedback mechanisms from the environment can modify these probabilities over time, enabling the system to adapt its behavior dynamically in response to positive or negative reinforcement based on its decisions. This system thus acts as a form of operant conditioning of the chemical circuit, in the sense that feedback provided based on decisions taken by the circuit form the basis of the learning process. Our work thus demonstrates that simple chemical systems can be used to implement lifelike behavior in engineered biomimetic systems.
MeSH term(s)	Conditioning, Operant ; Learning ; Adaptation, Psychological ; Artificial Cells ; Biomimetics
Language	English
Publishing date	2022-11-18
Publishing country	United States
Document type	Journal Article
ZDB-ID	2193340-6
ISSN	1553-7358 ; 1553-734X
ISSN (online)	1553-7358
ISSN	1553-734X
DOI	10.1371/journal.pcbi.1010676
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Protecting Heterochiral DNA Nanostructures against Exonuclease-Mediated Degradation.

Mallette, Tracy L / Lakin, Matthew R

ACS synthetic biology

2022 Volume 11, Issue 7, Page(s) 2222–2228

Abstract: Heterochiral DNA nanotechnology employs nucleic acids of both chiralities to construct nanoscale devices for applications in the intracellular environment. Interacting directly with cellular nucleic acids can be done most easily using D-DNA of the ... ...

Abstract	Heterochiral DNA nanotechnology employs nucleic acids of both chiralities to construct nanoscale devices for applications in the intracellular environment. Interacting directly with cellular nucleic acids can be done most easily using D-DNA of the naturally occurring right-handed chirality; however, D-DNA is more vulnerable to degradation than enantiometric left-handed L-DNA. Here we report a novel combination of D-DNA and L-DNA nucleotides in triblock heterochiral copolymers, where the L-DNA domains act as protective caps on D-DNA domains. We demonstrate that the D-DNA components of strand displacement-based molecular circuits constructed using this technique resist exonuclease-mediated degradation during extended incubations in serum-supplemented media more readily than similar devices without the L-DNA caps. We show that this protection can be applied to both double-stranded and single-stranded circuit components. Our work enhances the state of the art for robust heterochiral circuit design and could lead to practical applications such as
MeSH term(s)	DNA/chemistry ; Exonucleases ; Nanostructures ; Nanotechnology/methods
Chemical Substances	DNA (9007-49-2) ; Exonucleases (EC 3.1.-)
Language	English
Publishing date	2022-06-24
Publishing country	United States
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ISSN	2161-5063
ISSN (online)	2161-5063
DOI	10.1021/acssynbio.2c00105
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Robust finite automata in stochastic chemical reaction networks.

Arredondo, David / Lakin, Matthew R

Royal Society open science

2021 Volume 8, Issue 12, Page(s) 211310

Abstract: Finite-state automata (FSA) are simple computational devices that can nevertheless illustrate interesting behaviours. We propose that FSA can be employed as control circuits for engineered stochastic biological and biomolecular systems. We present an ... ...

Abstract	Finite-state automata (FSA) are simple computational devices that can nevertheless illustrate interesting behaviours. We propose that FSA can be employed as control circuits for engineered stochastic biological and biomolecular systems. We present an implementation of FSA using counts of chemical species in the range of hundreds to thousands, which is relevant for the counts of many key molecules such as mRNAs in prokaryotic cells. The challenge here is to ensure a robust representation of the current state in the face of stochastic noise. We achieve this by using a multistable approximate majority algorithm to stabilize and store the current state of the system. Arbitrary finite state machines can thus be compiled into robust stochastic chemical automata. We present two variants: one that consumes its input signals to initiate state transitions and one that does not. We characterize the state change dynamics of these systems and demonstrate their application to solve the four-bit binary square root problem. Our work lays the foundation for the use of chemical automata as control circuits in bioengineered systems and biorobotics.
Language	English
Publishing date	2021-12-22
Publishing country	England
Document type	Journal Article
ZDB-ID	2787755-3
ISSN	2054-5703
ISSN	2054-5703
DOI	10.1098/rsos.211310
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: A bumpy road ahead for genetic biocontainment.

George, Dalton R / Danciu, Mark / Davenport, Peter W / Lakin, Matthew R / Chappell, James / Frow, Emma K

Nature communications

2024 Volume 15, Issue 1, Page(s) 650

Language	English
Publishing date	2024-01-20
Publishing country	England
Document type	Journal Article
ZDB-ID	2553671-0
ISSN	2041-1723 ; 2041-1723
ISSN (online)	2041-1723
ISSN	2041-1723
DOI	10.1038/s41467-023-44531-1
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Domain-Specific Programming Languages for Computational Nucleic Acid Systems.

Lakin, Matthew R / Phillips, Andrew

ACS synthetic biology

2020 Volume 9, Issue 7, Page(s) 1499–1513

Abstract: The construction of models of system behavior is of great importance throughout science and engineering. In bioengineering and bionanotechnology, these often take the form of dynamic models that specify the evolution of different species over time. To ... ...

Abstract	The construction of models of system behavior is of great importance throughout science and engineering. In bioengineering and bionanotechnology, these often take the form of dynamic models that specify the evolution of different species over time. To ensure that scientific observations and conclusions are consistent and that systems can be reliably engineered on the basis of model predictions, it is important that models of biomolecular systems can be constructed in a reliable, principled, and efficient manner. This review focuses on efforts to address this need by using domain-specific programming languages as the basis for custom design tools for researchers working on computational nucleic acid devices, where a domain-specific language is simply a programming language tailored to a particular application domain. The underlying thesis of our review is that there is a continuum of practical implementation strategies for computational nucleic acid systems, which can all benefit from appropriate domain-specific languages and software design tools. We emphasize the need for specialized yet flexible tools that can be realized using domain-specific languages that compile to more general-purpose representations.
MeSH term(s)	Algorithms ; DNA/chemistry ; DNA/metabolism ; Enzymes/metabolism ; Logic ; Nanotechnology ; Nucleic Acid Hybridization ; Programming Languages ; Synthetic Biology
Chemical Substances	Enzymes ; DNA (9007-49-2)
Language	English
Publishing date	2020-07-08
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ISSN	2161-5063
ISSN (online)	2161-5063
DOI	10.1021/acssynbio.0c00050
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Structure sampling for computational estimation of localized DNA interaction rates.

Kumar, Sarika / Weisburd, Julian M / Lakin, Matthew R

Scientific reports

2021 Volume 11, Issue 1, Page(s) 12730

Abstract: Molecular circuits implemented using molecular components tethered to a DNA tile nanostructure have certain advantages over solution-phase circuits. Tethering components in close proximity increases the speed of reactions by reducing diffusion and ... ...

Abstract	Molecular circuits implemented using molecular components tethered to a DNA tile nanostructure have certain advantages over solution-phase circuits. Tethering components in close proximity increases the speed of reactions by reducing diffusion and improves scalability by enabling reuse of identical DNA sequences at different locations in the circuit. These systems show great potential for practical applications including delivery of diagnostic and therapeutic molecular circuits to cells. When modeling such systems, molecular geometry plays an important role in determining whether the two species interact and at what rate. In this paper, we present an automated method for estimating reaction rates in tethered molecular circuits that takes the geometry of the tethered species into account. We probabilistically generate samples of structure distributions based on simple biophysical models and use these to estimate important parameters for kinetic models. This work provides a basis for subsequent enhanced modeling and design tools for localized molecular circuits.
MeSH term(s)	Computers, Molecular ; DNA/chemistry ; Nanostructures
Chemical Substances	DNA (9007-49-2)
Language	English
Publishing date	2021-06-16
Publishing country	England
Document type	Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-021-92145-8
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito