Internal coarse-graining of molecular systems Export

@article{citeulike:4278230, abstract = {10.1073/pnas.0809908106 Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein–protein interactions occur. These contexts specify molecular patterns that are usually less detailed than molecular species. Yet, the execution of rule-based dynamics requires stochastic simulation, which can be very costly. It thus appears desirable to convert a rule-based model into a reduced system of differential equations by exploiting the granularity at which rules specify interactions. We present a formal (and automated) method for constructing a coarse-grained and self-consistent dynamical system aimed at molecular patterns that are distinguishable by the dynamics of the original system as posited by the rules. The method is formally sound and never requires the execution of the rule-based model. The coarse-grained variables do not depend on the values of the rate constants appearing in the rules, and typically form a system of greatly reduced dimension that can be amenable to numerical integration and further model reduction techniques.}, author = {Feret, J\'{e}r\^{o}me and Danos, Vincent and Krivine, Jean and Harmer, Russ and Fontana, Walter}, citeulike-article-id = {4278230}, citeulike-linkout-0 = {http://dx.doi.org/10.1073/pnas.0809908106}, citeulike-linkout-1 = {http://www.pnas.org/content/0809908106v1//.abstract}, citeulike-linkout-2 = {http://www.pnas.org/content/0809908106v1//.full.pdf}, citeulike-linkout-3 = {http://view.ncbi.nlm.nih.gov/pubmed/19346467}, citeulike-linkout-4 = {http://www.hubmed.org/display.cgi?uids=19346467}, day = {21}, doi = {10.1073/pnas.0809908106}, journal = {Proceedings of the National Academy of Sciences}, keywords = {graph\_theory, multiscale, systems\_biology}, month = {April}, number = {16}, pages = {6453--6458}, posted-at = {2009-04-23 12:31:17}, priority = {2}, title = {Internal coarse-graining of molecular systems}, url = {http://dx.doi.org/10.1073/pnas.0809908106}, volume = {106}, year = {2009} }

TY - JOUR ID - citeulike:4278230 L3 - citeulike-article-id:4278230 N2 - 10.1073/pnas.0809908106 Modelers of molecular signaling networks must cope with the combinatorial explosion of protein states generated by posttranslational modifications and complex formation. Rule-based models provide a powerful alternative to approaches that require explicit enumeration of all possible molecular species of a system. Such models consist of formal rules stipulating the (partial) contexts wherein specific protein–protein interactions occur. These contexts specify molecular patterns that are usually less detailed than molecular species. Yet, the execution of rule-based dynamics requires stochastic simulation, which can be very costly. It thus appears desirable to convert a rule-based model into a reduced system of differential equations by exploiting the granularity at which rules specify interactions. We present a formal (and automated) method for constructing a coarse-grained and self-consistent dynamical system aimed at molecular patterns that are distinguishable by the dynamics of the original system as posited by the rules. The method is formally sound and never requires the execution of the rule-based model. The coarse-grained variables do not depend on the values of the rate constants appearing in the rules, and typically form a system of greatly reduced dimension that can be amenable to numerical integration and further model reduction techniques. IS - 16 JF - Proceedings of the National Academy of Sciences EP - 6458 TI - Internal coarse-graining of molecular systems VL - 106 SP - 6453 KW - graph_theory KW - multiscale KW - systems_biology AU - Feret, Jérôme AU - Danos, Vincent AU - Krivine, Jean AU - Harmer, Russ AU - Fontana, Walter PY - 2009/04/21/ UR - http://dx.doi.org/10.1073/pnas.0809908106 ER -