Modelling biological systems
[2] An unexpected emergent property of a complex system may be a result of the interplay of the cause-and-effect among simpler, integrated parts (see biological organisation).Traditional study of biological systems requires reductive methods in which quantities of data are gathered by category, such as concentration over time in response to a certain stimulus.By far the most widely accepted standard format for storing and exchanging models in the field is the Systems Biology Markup Language (SBML).[4] The complex network of biochemical reaction/transport processes and their spatial organization make the development of a predictive model of a living cell a grand challenge for the 21st century, listed as such by the National Science Foundation (NSF) in 2006.There are a number of sub-projects, including the Cajal Blue Brain, coordinated by the Supercomputing and Visualization Center of Madrid (CeSViMa), and others run by universities and independent laboratories in the UK, U.S., and Israel.[11][12] It is one of six pilot projects in the Future Emerging Technologies Research Program of the European Commission,[13] competing for a billion euro funding.Typically they simplify complex foodwebs down to their major components or trophic levels, and quantify these as either numbers of organisms, biomass or the inventory/concentration of some pertinent chemical element (for instance, carbon or a nutrient species such as nitrogen or phosphorus).
systems biologymathematical biologyalgorithmsdata structuresvisualizationcomputer modellingcomputer simulationscellularnetworks of metabolitesenzymesmetabolismsignal transductiongene regulatory networksemergent propertycomplex systembiological organisation Systems Biology Markup Language (SBML)BioModelsBioPAXCellMLCellular modelcell cycletime-seriesLotka–Volterra modelcyclic behaviourtranscriptiontranslationpredictive modelNational Science FoundationMycoplasma genitaliumMembrane computingcell membraneOpenWormProtein folding problemproteinamino acidtertiary structureprimary structurebioinformaticstheoretical chemistryProtein structure predictionmedicinedrug designbiotechnologyBlue Brain Projectreverse-engineeringmammalian brainÉcole PolytechniqueLausanneBlue GenesupercomputerNEURON softwareartificial neural networkneuronsconsciousnessCajal Blue BrainSupercomputing and Visualization Center of MadridphysiologySimulated growth of plantsL-systemscomplexity scienceA-lifeEcosystem modelmathematicalecosystemsfoodwebstrophic levelsorganismsbiomassinventoryconcentrationchemical elementcarbonnutrientspeciesnitrogenphosphorusecotoxicologyMathematical modelling of infectious diseaseEpidemic modelepidemicvaccinationparametersinfectious diseasesBiological data visualizationBiosimulationGillespie algorithmMolecular modelling softwareStochastic simulationWayback MachineBibcodeCiteSeerXScientific modellingChemical process modelingInfectious disease modelMetabolic network modellingAtmospheric modelChemical transport modelClimate modelGeologic modellingGroundwater modelHydrological modelHydrological transport modelModular Ocean ModelWildfire modelingEnergy modelingIntegrated assessment modellingPopulation modelBiopsychosocial modelBusiness process modellingCatastrophe modelingConstruction and management simulationCrime mappingEconomic modelInput–output modelData visualizationList of computer simulation softwareMathematical modelingSystems theorySystems thinkingVisual analyticsComputational scienceBiologyAnatomyCognitionGenomics