Towards human cell simulation

Simone Spolaor, Marco Gribaudo, Mauro Iacono, Tomas Kadavy, Zuzana Komínková Oplatková, Giancarlo Mauri, Sabri Pllana, Roman Senkerik, Natalija Stojanovic, Esko Turunen, Adam Viktorin, Salvatore Vitabile, Aleš Zamuda, Marco S. Nobile

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureHoofdstukAcademicpeer review

7 Citaten (Scopus)
8 Downloads (Pure)

Samenvatting

The faithful reproduction and accurate prediction of the phenotypes and emergent behaviors of complex cellular systems are among the most challenging goals in Systems Biology. Although mathematical models that describe the interactions among all biochemical processes in a cell are theoretically feasible, their simulation is generally hard because of a variety of reasons. For instance, many quantitative data (e.g., kinetic rates) are usually not available, a problem that hinders the execution of simulation algorithms as long as some parameter estimation methods are used. Though, even with a candidate parameterization, the simulation of mechanistic models could be challenging due to the extreme computational effort required. In this context, model reduction techniques and High-Performance Computing infrastructures could be leveraged to mitigate these issues. In addition, as cellular processes are characterized by multiple scales of temporal and spatial organization, novel hybrid simulators able to harmonize different modeling approaches (e.g., logic-based, constraint-based, continuous deterministic, discrete stochastic, spatial) should be designed. This chapter describes a putative unified approach to tackle these challenging tasks, hopefully paving the way to the definition of large-scale comprehensive models that aim at the comprehension of the cell behavior by means of computational tools.
Originele taal-2Engels
TitelHigh-performance modelling and simulation for big data applications
Subtitelselected results of the COST action IC1406 cHiPSet
RedacteurenJoanna Kołodziej , Horacio González-Vélez
UitgeverijSpringer
Pagina's221-249
Aantal pagina's29
ISBN van elektronische versie978-3-030-16272-6
ISBN van geprinte versie978-3-030-16271-9
DOI's
StatusGepubliceerd - 31 mrt 2019
Extern gepubliceerdJa

Publicatie series

NaamLecture Notes in Computer Science
UitgeverijSpringer
Volume11400

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