Biomedical research is becoming increasingly dependent on construction and simulation of computational models.Arguablythiswillbeevenmorethecasewiththedevelopmentofpersonalizedmedicine.However, thetechnicalaspectsofmodelingandsimulationareoverwhelmingtomanybiomedicalresearchers.Whatis neededisasoftwareapplicationcapableofprovidingtheappropriatenumericalalgorithms,butshieldedbya user interface that aides the biomedical researcher in conducting the required simulations. Modeling and simulation can be applied at the level of molecules, their networks, cells, tissues and whole organisms. Sometimesseveraloftheselevelshavetoberepresentedinordertoproperlypredictandunderstandhealth and disease. Thus models are becoming larger, multiscale, and require various different mathematical frameworks for simulation. We propose to address this need with continuing development of the COPASI software,whichisalreadywidelyusedinthebiomedicalresearchcommunity,addressingthecurrenttrends. ThisprojectwillalsoprovidesupporttothevibrantcommunityofCOPASIusers/biomedicalresearchers.We willaddressthiswiththefollowingSpecificAims:
Aim1. Addnewnumericalsimulationandanalysismethodstofurthersupportbiomedicalresearch.Wewill develop and add new hybrid simulation algorithms to address models that require some of its parts to be simulatedindifferentframeworks.Wewilladdanewtasktoanalyzeparameteridentifiability,whichisvery usefulforfindingoutifthemodelanddataarematched,orimprovementsneedtobemadeinboth.
Aim2. ImproveCOPASI?suserinterfaceandtheinterfaceswithothersoftware.Wewillimprovethegraphical user interface to allow it to efficiently manipulate very large models. We will create a new programming interfacesothatotherscaneasilyuseCOPASI?sfunctionsfromotherprograms.
Aim3. Softwaremaintenanceandstandardscompliance.Wewillcontinuetomaintainthesoftware,correcting errorsandmakingimprovements,guidedbyfeedbackcollectedfromitsusers.Wewillcontinuetoimplement standardscompliancetoensurethesoftwareisinteroperablewithotherapplications.
Aim 4. Support the modeling community. We will continue outreach program activities aimed helping biomedicalresearchersmakefulluseofthesoftware?scapabilities.Thisincludescontinuingtooffertutorials, courses,andworkshops?tocreatefurthertrainingvideosandtomaintainawebbaseddiscussiongroup.

Public Health Relevance

This research will focus on developing and maintaining the COPASI software, a tool for studying complex biological systems, including human disease models, through computer simulation. COPASI will facilitate knowledge discovery using computer simulations that are important in health and disease, including drug design,andpersonalizedmedicine.Useofthissoftwarewillbeavailabletoallbiomedicalresearcherswithout limitationandwillcontributetounderstandinghowdiseasesdevelopandhowtheycanbecured.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Biodata Management and Analysis Study Section (BDMA)
Program Officer
Brazhnik, Paul
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University of Virginia
United States
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Mendes, Pedro (2018) Reproducible Research Using Biomodels. Bull Math Biol 80:3081-3087
Parmar, Jignesh H; Quintana, Julia; Ramírez, David et al. (2018) An important role for periplasmic storage in Pseudomonas aeruginosa copper homeostasis revealed by a combined experimental and computational modeling study. Mol Microbiol 110:357-369
Gupta, Abhishekh; Mendes, Pedro (2018) An Overview of Network-Based and -Free Approaches for Stochastic Simulation of Biochemical Systems. Computation (Basel) 6:
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Verma, Meghna; Erwin, Samantha; Abedi, Vida et al. (2017) Modeling the Mechanisms by Which HIV-Associated Immunosuppression Influences HPV Persistence at the Oral Mucosa. PLoS One 12:e0168133
Millard, Pierre; Smallbone, Kieran; Mendes, Pedro (2017) Metabolic regulation is sufficient for global and robust coordination of glucose uptake, catabolism, energy production and growth in Escherichia coli. PLoS Comput Biol 13:e1005396
Dacheux, Estelle; Malys, Naglis; Meng, Xiang et al. (2017) Translation initiation events on structured eukaryotic mRNAs generate gene expression noise. Nucleic Acids Res 45:6981-6992
Meng, Xiang; Firczuk, Helena; Pietroni, Paola et al. (2017) Minimum-noise production of translation factor eIF4G maps to a mechanistically determined optimal rate control window for protein synthesis. Nucleic Acids Res 45:1015-1025
Swainston, Neil; Smallbone, Kieran; Hefzi, Hooman et al. (2016) Recon 2.2: from reconstruction to model of human metabolism. Metabolomics 12:109
Millard, Pierre; Portais, Jean-Charles; Mendes, Pedro (2015) Impact of kinetic isotope effects in isotopic studies of metabolic systems. BMC Syst Biol 9:64

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