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Practicing Safe Modeling: GLP for Biologically Based Mechanistic Models

Christopher J. Portier, Cynthia M. Lyles
1996 Environmental Health Perspectives  
Using GLP in model development and application should alleviate this problem.  ...  There is general belief that if the analysis is based upon a model with some biological underpinning, it will provide better risk estimates than an empirical model.  ...  There is general belief that if the analysis is based upon a model with some biological underpinning, it will provide better risk estimates than an empirical model.  ... 
doi:10.2307/3432921 fatcat:z6ruu2agifd5jabhvx6qdnzzse

Practicing safe modeling: GLP for biologically based mechanistic models

C J Portier, C M Lyles
1996 Environmental Health Perspectives  
Using GLP in model development and application should alleviate this problem.  ...  There is general belief that if the analysis is based upon a model with some biological underpinning, it will provide better risk estimates than an empirical model.  ...  There is general belief that if the analysis is based upon a model with some biological underpinning, it will provide better risk estimates than an empirical model.  ... 
doi:10.1289/ehp.96104806 pmid:8875144 pmcid:PMC1469438 fatcat:xbnouor7ffcyzh6ftvwv5yiely

Biological Computation as the Revolution of Complex Engineered Systems [article]

Nelson Alfonso Gómez-Cruz, Carlos Eduardo Maldonado
2011 arXiv   pre-print
Bio-inspired engineering and CES thereafter, must turn its regard toward biological computation.  ...  A remark is needed here: P versus NP problems should be well defined and delimited but biological computation problems are not.  ...  Biological computation, hypercomputation, complex computations, biochemical processes, and some non-classical logics emerge as new tools and explications for what a living being is and can do to adapt  ... 
arXiv:1110.3316v1 fatcat:p6qzrwluwvgjtmtxsljbxifq74

Page 8856 of Mathematical Reviews Vol. , Issue 2003k [page]

2003 Mathematical Reviews  
We discuss the problem of carrying out computations in circuits consisting of biologically realistic computational units, focusing on the biologically partic- ularly relevant case of computations on time  ...  Summary: “We discuss in this short survey article some current mathematical models from neurophysiology for the computational units of biological neural systems: neurons and synapses.  ... 

Information as Order Hidden within Chance: An Application to Biology

Strumia A
2019 Physical Science & Biophysics Journal  
In absence of information emergence of some ordered structure, like e.g., an organ of a living system is so highly improbable to be impossible in practice.  ...  In our example of anatomic human heart model we have treated the sequence of the co-ordinates of each sphere (roughly modeling a cell) as an uncompressed string, while a compressed program string seems  ...  In this framework at least two main problems arise. How to define information and how to try to provide a model of information behavior?  ... 
doi:10.23880/psbj-16000126 fatcat:empsab7z2jhrhd3sklmnyiflwm

Computation by natural systems

Dominique Chu, Mikhail Prokopenko, J. Christian J. Ray
2018 Interface Focus  
One contribution of 10 to a theme issue 'Computation by natural systems'. Subject Areas: computational biology  ...  Nevertheless it lurks in the background and is the driving force for how natural computations arise in biology.  ...  FSMs are a non-universal model of computation that has significant importance in computer science.  ... 
doi:10.1098/rsfs.2018.0058 fatcat:3if6iqsaejahzoazlpro3nhd2y

Levels of biological plausibility

Bradley C. Love
2020 Philosophical Transactions of the Royal Society of London. Biological Sciences  
Claims of biological plausibility are shown to be incoherent from a level of mechanism view and more generally are vacuous.  ...  Model selection can help reduce theoretical confusions and direct empirical investigations.  ...  A charitable interpretation is that claimants of biological plausibility have some dataset in mind that their model addresses that some other model does not.  ... 
doi:10.1098/rstb.2019.0632 pmid:33190602 fatcat:qux7suqjtfgqnfrujzdkgmvpee

How Not to Evaluate a Developmental System

F. Shic, B. Scassellati
2006 The 2006 IEEE International Joint Conference on Neural Network Proceedings  
of model fitness; and 3) don't hide or reject variation as found in the computational model.  ...  In particular we focus on the following recommendations: 1) don't equate the success of a developmental model with its peak performance at some task; 2) don't employ purely subjective or qualitative measures  ...  It is a natural reaction to believe that a computational model matches biological reality when some measurable surface characteristic of the computational model behaves in some biologically plausible fashion  ... 
doi:10.1109/ijcnn.2006.247275 dblp:conf/ijcnn/ShicS06 fatcat:7hh2lbpqszcshfpjgqoskiorgm

Page 7380 of Mathematical Reviews Vol. , Issue 87m [page]

1987 Mathematical Reviews  
Summary (translated from the Russian): “We formulate basic mathematical problems of computer diagnostics.  ...  Summary: “In recent years some progress has been made in mo- delling pattern formation and morphogenesis in biological systems in terms of calcium ion regulation of the viscoelastic properties of the cellular  ... 

PREFACE — CHALLENGING MATHEMATICAL PROBLEMS IN CANCER MODELLING

N. BELLOMO, P. K. MAINI
2007 Mathematical Models and Methods in Applied Sciences  
This issue, the third (and final) of a series in this journal devoted to cancer modeling, is focused on analytic problems arising from the application of mathematical models to the simulation of biological  ...  The contents of the preceding issues are described in the Prefaces. 7, 8 In some cases, the qualitative and computational analyses of problems need the development of sophisticated mathematical methods  ...  This issue, the third (and final) of a series in this journal devoted to cancer modeling, is focused on analytic problems arising from the application of mathematical models to the simulation of biological  ... 
doi:10.1142/s0218202507002418 fatcat:kweeqxhncngwpg6l5k6rok73ey

PITFALLS IN THE MODELING OF DEVELOPMENTAL SYSTEMS

FREDERICK SHIC, BRIAN SCASSELLATI
2007 International Journal of Humanoid Robotics  
of model fitness; and 3) don't hide or reject variation as found in the computational model.  ...  In particular we focus on the following recommendations: 1) don't equate the success of a developmental model with its peak performance at some task; 2) don't employ purely subjective or vague measures  ...  Some parts of the architecture used in this work was  ... 
doi:10.1142/s0219843607001084 fatcat:y3jnqrcyffcb7m7xp3zb3yoxte

Page 1224 of Mathematical Reviews Vol. , Issue 89B [page]

1989 Mathematical Reviews  
The considered problems include chemotaxis (i.e., the drift of organisms towards (as opposed to “from”) relatively high concentrations of chemical attractants), biological waves in inhomogeneous media,  ...  They are found to be quite versatile in modeling the self-organization of biological systems.  ... 

Systems biology: a way to make complex problems more understandable

I N Lavrik, B Zhivotovsky
2014 Cell Death and Disease  
Modeling cell-to-cell variations arising from single-cell measurements requires stochastic simulations.  ...  Computational models require the exact knowledge about the numbers and interaction constants of the molecules in the pathway that allows making unique quantitative assessments upon molecular mechanisms  ...  The work in the authors group was supported by grants from the Swedish and the Stockholm Cancer Societies, the Swedish Childhood Cancer  ... 
doi:10.1038/cddis.2014.195 pmid:24874728 pmcid:PMC4047879 fatcat:yfjvghw3ofge5jqukb5bfpv3gq

Hybridization Concepts of Artificial Human Optimization Field Algorithms Incorporated into Particle Swarm Optimization

Hassan M., Satish Gajawada
2018 International Journal of Computer Applications  
This piece of research presents the Particle Swarm Optimization (PSO) as a biologically inspired computational paradigm searches for problem optimization technique.  ...  More precisely it is a population-based, stochastic algorithm modeled on the social behaviors observed in flocking birds.  ...  well as large size optimization problem arising in different fields.  ... 
doi:10.5120/ijca2018917866 fatcat:uginqiijxrgsxemh2mwal55yea
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