Logic modeling and the ridiculome under the rug

<p>Abstract</p> <p>Logic-derived modeling has been used to map biological networks and to study arbitrary functional interactions, and fine-grained kinetic modeling can accurately predict the detailed behavior of well-characterized molecular systems; at present, however, neither ap...

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Main Authors: Blinov Michael L, Moraru Ion I
Format: Article
Language:English
Published: BMC 2012-11-01
Series:BMC Biology
Online Access:http://www.biomedcentral.com/1741-7007/10/92
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author Blinov Michael L
Moraru Ion I
author_facet Blinov Michael L
Moraru Ion I
author_sort Blinov Michael L
collection DOAJ
description <p>Abstract</p> <p>Logic-derived modeling has been used to map biological networks and to study arbitrary functional interactions, and fine-grained kinetic modeling can accurately predict the detailed behavior of well-characterized molecular systems; at present, however, neither approach comes close to unraveling the full complexity of a cell. The current data revolution offers significant promises and challenges to both approaches - and could bring them together as it has spurred the development of new methods and tools that may help to bridge the many gaps between data, models, and mechanistic understanding.</p> <p>Have you used logic modeling in your research? It would not be surprising if many biologists would answer no to this hypothetical question. And it would not be true. In high school biology we already became familiar with cartoon diagrams that illustrate basic mechanisms of the molecular machinery operating inside cells. These are nothing else but simple logic models. If receptor and ligand are present, then receptor-ligand complexes form; if a receptor-ligand complex exists, then an enzyme gets activated; if the enzyme is active, then a second messenger is being produced; and so on. Such chains of causality are the essence of logic models (Figure 1a). Arbitrary events and mechanisms are abstracted; relationships are simplified and usually involve just two possible conditions and three possible consequences. The presence or absence of one or more molecule, activity, or function, [some icons in the cartoon] will determine whether another one of them will be produced (created, up-regulated, stimulated) [a 'positive' link] or destroyed (degraded, down-regulated, inhibited) [a 'negative' link], or be unaffected [there is no link]. The icons and links often do not follow a standardized format, but when we look at such a cartoon diagram, we believe that we 'understand' how the system works. Because our brain is easily able to process these relationships, these diagrams allow us to answer two fundamental types of questions related to the system: why (are certain things happening)? What if (we make some changes)?</p>
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spelling doaj.art-d6ba6c9a865c46a89858f6cb9a7124cb2022-12-22T00:27:48ZengBMCBMC Biology1741-70072012-11-011019210.1186/1741-7007-10-92Logic modeling and the ridiculome under the rugBlinov Michael LMoraru Ion I<p>Abstract</p> <p>Logic-derived modeling has been used to map biological networks and to study arbitrary functional interactions, and fine-grained kinetic modeling can accurately predict the detailed behavior of well-characterized molecular systems; at present, however, neither approach comes close to unraveling the full complexity of a cell. The current data revolution offers significant promises and challenges to both approaches - and could bring them together as it has spurred the development of new methods and tools that may help to bridge the many gaps between data, models, and mechanistic understanding.</p> <p>Have you used logic modeling in your research? It would not be surprising if many biologists would answer no to this hypothetical question. And it would not be true. In high school biology we already became familiar with cartoon diagrams that illustrate basic mechanisms of the molecular machinery operating inside cells. These are nothing else but simple logic models. If receptor and ligand are present, then receptor-ligand complexes form; if a receptor-ligand complex exists, then an enzyme gets activated; if the enzyme is active, then a second messenger is being produced; and so on. Such chains of causality are the essence of logic models (Figure 1a). Arbitrary events and mechanisms are abstracted; relationships are simplified and usually involve just two possible conditions and three possible consequences. The presence or absence of one or more molecule, activity, or function, [some icons in the cartoon] will determine whether another one of them will be produced (created, up-regulated, stimulated) [a 'positive' link] or destroyed (degraded, down-regulated, inhibited) [a 'negative' link], or be unaffected [there is no link]. The icons and links often do not follow a standardized format, but when we look at such a cartoon diagram, we believe that we 'understand' how the system works. Because our brain is easily able to process these relationships, these diagrams allow us to answer two fundamental types of questions related to the system: why (are certain things happening)? What if (we make some changes)?</p>http://www.biomedcentral.com/1741-7007/10/92
spellingShingle Blinov Michael L
Moraru Ion I
Logic modeling and the ridiculome under the rug
BMC Biology
title Logic modeling and the ridiculome under the rug
title_full Logic modeling and the ridiculome under the rug
title_fullStr Logic modeling and the ridiculome under the rug
title_full_unstemmed Logic modeling and the ridiculome under the rug
title_short Logic modeling and the ridiculome under the rug
title_sort logic modeling and the ridiculome under the rug
url http://www.biomedcentral.com/1741-7007/10/92
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AT moraruioni logicmodelingandtheridiculomeundertherug