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  1. Article ; Online: Design patterns of biological cells.

    Andrews, Steven S / Wiley, H Steven / Sauro, Herbert M

    BioEssays : news and reviews in molecular, cellular and developmental biology

    2024  Volume 46, Issue 3, Page(s) e2300188

    Abstract: Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to ... ...

    Abstract Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.
    MeSH term(s) Escherichia coli/genetics ; Escherichia coli/metabolism ; Signal Transduction ; Metabolic Networks and Pathways ; Models, Biological
    Language English
    Publishing date 2024-01-21
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 50140-2
    ISSN 1521-1878 ; 0265-9247
    ISSN (online) 1521-1878
    ISSN 0265-9247
    DOI 10.1002/bies.202300188
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  2. Article ; Online: Design Patterns of Biological Cells.

    Andrews, Steven S / Wiley, H Steven / Sauro, Herbert M

    ArXiv

    2023  

    Abstract: Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology in ... ...

    Abstract Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology in order to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.
    Language English
    Publishing date 2023-10-11
    Publishing country United States
    Document type Preprint
    ISSN 2331-8422
    ISSN (online) 2331-8422
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  3. Article ; Online: Effects of surfaces and macromolecular crowding on bimolecular reaction rates.

    Andrews, Steven S

    Physical biology

    2020  Volume 17, Issue 4, Page(s) 45001

    Abstract: Biological cells are complex environments that are densely packed with macromolecules and subdivided by membranes, both of which affect the rates of chemical reactions. It is well known that crowding reduces the volume available to reactants, which ... ...

    Abstract Biological cells are complex environments that are densely packed with macromolecules and subdivided by membranes, both of which affect the rates of chemical reactions. It is well known that crowding reduces the volume available to reactants, which increases reaction rates, and also inhibits reactant diffusion, which decreases reaction rates. This work investigates these effects quantitatively using analytical theory and particle-based simulations. A reaction rate equation based on only these two processes turned out to be inconsistent with simulation results. However, accounting for diffusion inhibition by the surfaces of nearby obstacles, which affects access to reactants, it led to perfect agreement for reactions near impermeable planar membranes and improved agreement for reactions in crowded spaces. A separate model that quantified reactant occlusion by crowders, and extensions to a thermodynamic 'cavity' model proposed by Berezhkovskii and Szabo [25], were comparably successful. These results help elucidate reaction dynamics in confined spaces and improve prediction of in vivo reaction rates from in vitro ones.
    MeSH term(s) Diffusion ; Macromolecular Substances/chemistry ; Models, Molecular ; Particle Size ; Surface Properties ; Thermodynamics
    Chemical Substances Macromolecular Substances
    Language English
    Publishing date 2020-05-15
    Publishing country England
    Document type Journal Article
    ZDB-ID 2133216-2
    ISSN 1478-3975 ; 1478-3967
    ISSN (online) 1478-3975
    ISSN 1478-3967
    DOI 10.1088/1478-3975/ab7f51
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  4. Article ; Online: Rule-Based Modeling Using Wildcards in the Smoldyn Simulator.

    Andrews, Steven S

    Methods in molecular biology (Clifton, N.J.)

    2019  Volume 1945, Page(s) 179–202

    Abstract: Many biological molecules exist in multiple variants, such as proteins with different posttranslational modifications, DNAs with different sequences, and phospholipids with different chain lengths. Representing these variants as distinct species, as most ...

    Abstract Many biological molecules exist in multiple variants, such as proteins with different posttranslational modifications, DNAs with different sequences, and phospholipids with different chain lengths. Representing these variants as distinct species, as most biochemical simulators do, leads to the problem that the number of species, and chemical reactions that interconvert them, typically increase combinatorially with the number of ways that the molecules can vary. This can be alleviated by "rule-based modeling methods," in which software generates the chemical reaction network from relatively simple "rules." This chapter presents a new approach to rule-based modeling. It is based on wildcards that match to species names, much as wildcards can match to file names in computer operating systems. It is much simpler to use than the formal rule-based modeling approaches developed previously but can lead to unintended consequences if not used carefully. This chapter demonstrates rule-based modeling with wildcards through examples for signaling systems, protein complexation, polymerization, nucleic acid sequence copying and mutation, the "SMILES" chemical notation, and others. The method is implemented in Smoldyn, a spatial and stochastic biochemical simulator, for both generate-first and on-the-fly expansion, meaning whether the reaction network is generated before or during the simulation.
    MeSH term(s) Computational Biology/methods ; Computer Simulation ; DNA/chemistry ; DNA/genetics ; Models, Biological ; Signal Transduction/genetics ; Software
    Chemical Substances DNA (9007-49-2)
    Language English
    Publishing date 2019-04-03
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1940-6029
    ISSN (online) 1940-6029
    DOI 10.1007/978-1-4939-9102-0_8
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online: Design Patterns of Biological Cells

    Andrews, Steven S. / Wiley, H. Steven / Sauro, Herbert M.

    2023  

    Abstract: Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology in ... ...

    Abstract Design patterns are generalized solutions to frequently recurring problems. They were initially developed by architects and computer scientists to create a higher level of abstraction for their designs. Here, we extend these concepts to cell biology in order to lend a new perspective on the evolved designs of cells' underlying reaction networks. We present a catalog of 21 design patterns divided into three categories: creational patterns describe processes that build the cell, structural patterns describe the layouts of reaction networks, and behavioral patterns describe reaction network function. Applying this pattern language to the E. coli central metabolic reaction network, the yeast pheromone response signaling network, and other examples lends new insights into these systems.
    Keywords Quantitative Biology - Molecular Networks
    Publishing date 2023-10-11
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: Python interfaces for the Smoldyn simulator.

    Singh, Dilawar / Andrews, Steven S

    Bioinformatics (Oxford, England)

    2021  Volume 38, Issue 1, Page(s) 291–293

    Abstract: Motivation: Smoldyn is a particle-based biochemical simulator that is frequently used for systems biology and biophysics research. Previously, users could only define models using text-based input or a C/C++ application programming interface (API), ... ...

    Abstract Motivation: Smoldyn is a particle-based biochemical simulator that is frequently used for systems biology and biophysics research. Previously, users could only define models using text-based input or a C/C++ application programming interface (API), which were convenient, but limited extensibility.
    Results: We added a Python API to Smoldyn to improve integration with other software tools, such as Jupyter notebooks, other Python code libraries and other simulators. It includes low-level functions that closely mimic the existing C/C++ API and higher-level functions that are more convenient to use. These latter functions follow modern object-oriented Python conventions.
    Availability and implementation: Smoldyn is open source and free, available at http://www.smoldyn.org and can be installed with the Python package manager pip. It runs on Mac, Windows and Linux.
    Documentation is available at http://www.smoldyn.org/SmoldynManual.pdf and https://smoldyn.readthedocs.io/en/latest/python/api.html.
    MeSH term(s) Software ; Systems Biology ; Documentation
    Language English
    Publishing date 2021-07-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btab530
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  7. Article ; Online: Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface.

    Andrews, Steven S

    Bioinformatics (Oxford, England)

    2017  Volume 33, Issue 5, Page(s) 710–717

    Abstract: ... steven.s.andrews@gmail.com. ...

    Abstract Motivation: Smoldyn is a spatial and stochastic biochemical simulator. It treats each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions and chemical reactions, all with good accuracy. This article presents several new features.
    Results: Smoldyn now supports two types of rule-based modeling. These are a wildcard method, which is very convenient, and the BioNetGen package with extensions for spatial simulation, which is better for complicated models. Smoldyn also includes new algorithms for simulating the diffusion of surface-bound molecules and molecules with excluded volume. Both are exact in the limit of short time steps and reasonably good with longer steps. In addition, Smoldyn supports single-molecule tracking simulations. Finally, the Smoldyn source code can be accessed through a C/C ++ language library interface.
    Availability and implementation: Smoldyn software, documentation, code, and examples are at http://www.smoldyn.org .
    Contact: steven.s.andrews@gmail.com.
    Language English
    Publishing date 2017-03-01
    Publishing country England
    Document type Journal Article
    ZDB-ID 1422668-6
    ISSN 1367-4811 ; 1367-4803
    ISSN (online) 1367-4811
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btw700
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  8. Article: Dynamics and Sensitivity of Signaling Pathways.

    Kochen, Michael A / Andrews, Steven S / Wiley, H Steven / Feng, Song / Sauro, Herbert M

    Current pathobiology reports

    2022  Volume 10, Issue 2, Page(s) 11–22

    Abstract: Purpose of review: Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are ... ...

    Abstract Purpose of review: Signaling pathways serve to communicate information about extracellular conditions into the cell, to both the nucleus and cytoplasmic processes to control cell responses. Genetic mutations in signaling network components are frequently associated with cancer and can result in cells acquiring an ability to divide and grow uncontrollably. Because signaling pathways play such a significant role in cancer initiation and advancement, their constituent proteins are attractive therapeutic targets. In this review, we discuss how signaling pathway modeling can assist with identifying effective drugs for treating diseases, such as cancer. An achievement that would facilitate the use of such models is their ability to identify controlling biochemical parameters in signaling pathways, such as molecular abundances and chemical reaction rates, because this would help determine effective points of attack by therapeutics.
    Recent findings: We summarize the current state of understanding the sensitivity of phosphorylation cycles with and without sequestration. We also describe some basic properties of regulatory motifs including feedback and feedforward regulation.
    Summary: Although much recent work has focused on understanding the dynamics and particularly the sensitivity of signaling networks in eukaryotic systems, there is still an urgent need to build more scalable models of signaling networks that can appropriately represent their complexity across different cell types and tumors.
    Language English
    Publishing date 2022-06-27
    Publishing country United States
    Document type Journal Article
    ISSN 2167-485X
    ISSN 2167-485X
    DOI 10.1007/s40139-022-00230-y
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  9. Article: Smoldyn: particle-based simulation with rule-based modeling, improved molecular interaction and a library interface

    Andrews, Steven S

    Bioinformatics. 2017 Mar. 01, v. 33, no. 5

    2017  

    Abstract: ... Smoldyn software, documentation, code, and examples are at http://www.smoldyn.org. Contact: steven.s ... andrews@gmail.com ...

    Abstract Motivation: Smoldyn is a spatial and stochastic biochemical simulator. It treats each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions and chemical reactions, all with good accuracy. This article presents several new features. Results: Smoldyn now supports two types of rule-based modeling. These are a wildcard method, which is very convenient, and the BioNetGen package with extensions for spatial simulation, which is better for complicated models. Smoldyn also includes new algorithms for simulating the diffusion of surface-bound molecules and molecules with excluded volume. Both are exact in the limit of short time steps and reasonably good with longer steps. In addition, Smoldyn supports single-molecule tracking simulations. Finally, the Smoldyn source code can be accessed through a C/C ++ language library interface. Availability and Implementation: Smoldyn software, documentation, code, and examples are at http://www.smoldyn.org. Contact: steven.s.andrews@gmail.com
    Keywords algorithms ; bioinformatics ; chemical reactions ; computer software ; models
    Language English
    Dates of publication 2017-0301
    Size p. 710-717.
    Publishing place Oxford University Press
    Document type Article
    ZDB-ID 1468345-3
    ISSN 1460-2059 ; 1367-4803
    ISSN (online) 1460-2059
    ISSN 1367-4803
    DOI 10.1093/bioinformatics/btw700
    Database NAL-Catalogue (AGRICOLA)

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  10. Article ; Online: Nutri: A Behavioral Science-Based Clinical Decision Support for Chronic Disease Management.

    Burgermaster, Marissa / Rosenthal, Madalyn / Tierney, William M / Altillo, Brandon S / Nordquist, Eric / Enriquez, Christina / Andrews, Steven / Klatt, Caroline / Daniels, Grant

    AMIA ... Annual Symposium proceedings. AMIA Symposium

    2023  Volume 2022, Page(s) 299–308

    Abstract: ... perceptions of Nutri's value and usability. 100% of participating clinicians achieved Nutri's main objective ... Insights will improve Nutri's usability and clinical workflow integration. ...

    Abstract Clinical decision support systems (CDSS) for the ongoing decision making required to support health behavior change for chronic disease management should incorporate behavioral science (e.g., a collaborative goal setting workflow) with more common CDSS components (i.e., an evidence-based knowledge base that processes patient data). Given known challenges with CDSS usability and adoption, engaging clinician end-users in designing new CDSS is vital. Therefore, we tested Nutri, a CDSS for collaborative diet goal setting, with 10 clinicians in a simulated primary care appointment with a patient actor. Simulation recordings, usability surveys, and debriefing interviews provided a multi-method view of clinicians' perceptions of Nutri's value and usability. 100% of participating clinicians achieved Nutri's main objective: selecting a high impact diet goal during a collaborative goal setting discussion with the patient; participants found Nutri usable, potentially timesaving, and increased their diet counseling self-efficacy. Insights will improve Nutri's usability and clinical workflow integration.
    MeSH term(s) Humans ; Decision Support Systems, Clinical ; Chronic Disease ; Surveys and Questionnaires ; Health Education ; Disease Management
    Language English
    Publishing date 2023-04-29
    Publishing country United States
    Document type Journal Article
    ISSN 1942-597X
    ISSN (online) 1942-597X
    Database MEDical Literature Analysis and Retrieval System OnLINE

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