FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2102434872> ?p ?o ?g. }

• W2102434872 endingPage "e74335" @default.
• W2102434872 startingPage "e74335" @default.
• W2102434872 abstract "Due to the high complexity of biological data it is difficult to disentangle cellular processes relying only on intuitive interpretation of measurements. A Systems Biology approach that combines quantitative experimental data with dynamic mathematical modeling promises to yield deeper insights into these processes. Nevertheless, with growing complexity and increasing amount of quantitative experimental data, building realistic and reliable mathematical models can become a challenging task: the quality of experimental data has to be assessed objectively, unknown model parameters need to be estimated from the experimental data, and numerical calculations need to be precise and efficient. Here, we discuss, compare and characterize the performance of computational methods throughout the process of quantitative dynamic modeling using two previously established examples, for which quantitative, dose- and time-resolved experimental data are available. In particular, we present an approach that allows to determine the quality of experimental data in an efficient, objective and automated manner. Using this approach data generated by different measurement techniques and even in single replicates can be reliably used for mathematical modeling. For the estimation of unknown model parameters, the performance of different optimization algorithms was compared systematically. Our results show that deterministic derivative-based optimization employing the sensitivity equations in combination with a multi-start strategy based on latin hypercube sampling outperforms the other methods by orders of magnitude in accuracy and speed. Finally, we investigated transformations that yield a more efficient parameterization of the model and therefore lead to a further enhancement in optimization performance. We provide a freely available open source software package that implements the algorithms and examples compared here." @default.
• W2102434872 created "2016-06-24" @default.
• W2102434872 creator A5020619230 @default.
• W2102434872 creator A5025232222 @default.
• W2102434872 creator A5033761148 @default.
• W2102434872 creator A5046026391 @default.
• W2102434872 creator A5052831097 @default.
• W2102434872 creator A5059275010 @default.
• W2102434872 creator A5061617505 @default.
• W2102434872 creator A5063153590 @default.
• W2102434872 creator A5063690344 @default.
• W2102434872 creator A5068735853 @default.
• W2102434872 creator A5076933919 @default.
• W2102434872 creator A5088311959 @default.
• W2102434872 date "2013-09-30" @default.
• W2102434872 modified "2023-10-17" @default.
• W2102434872 title "Lessons Learned from Quantitative Dynamical Modeling in Systems Biology" @default.
• W2102434872 cites W1484198052 @default.
• W2102434872 cites W1506397612 @default.
• W2102434872 cites W1600765471 @default.
• W2102434872 cites W1605961137 @default.
• W2102434872 cites W181733065 @default.
• W2102434872 cites W1975097468 @default.
• W2102434872 cites W1979181404 @default.
• W2102434872 cites W1980037861 @default.
• W2102434872 cites W1988093340 @default.
• W2102434872 cites W2032828164 @default.
• W2102434872 cites W2059246518 @default.
• W2102434872 cites W2071467620 @default.
• W2102434872 cites W2084840427 @default.
• W2102434872 cites W2087752119 @default.
• W2102434872 cites W2093931050 @default.
• W2102434872 cites W2111510713 @default.
• W2102434872 cites W2117057692 @default.
• W2102434872 cites W2131043603 @default.
• W2102434872 cites W2134221731 @default.
• W2102434872 cites W2138163236 @default.
• W2102434872 cites W2143894094 @default.
• W2102434872 cites W2151389393 @default.
• W2102434872 cites W2154602420 @default.
• W2102434872 cites W2164796316 @default.
• W2102434872 cites W2166751342 @default.
• W2102434872 cites W2168648059 @default.
• W2102434872 cites W3098527589 @default.
• W2102434872 cites W3102649939 @default.
• W2102434872 cites W4292691288 @default.
• W2102434872 doi "https://doi.org/10.1371/journal.pone.0074335" @default.
• W2102434872 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3787051" @default.
• W2102434872 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/24098642" @default.
• W2102434872 hasPublicationYear "2013" @default.
• W2102434872 type Work @default.
• W2102434872 sameAs 2102434872 @default.
• W2102434872 citedByCount "273" @default.
• W2102434872 countsByYear W21024348722013 @default.
• W2102434872 countsByYear W21024348722014 @default.
• W2102434872 countsByYear W21024348722015 @default.
• W2102434872 countsByYear W21024348722016 @default.
• W2102434872 countsByYear W21024348722017 @default.
• W2102434872 countsByYear W21024348722018 @default.
• W2102434872 countsByYear W21024348722019 @default.
• W2102434872 countsByYear W21024348722020 @default.
• W2102434872 countsByYear W21024348722021 @default.
• W2102434872 countsByYear W21024348722022 @default.
• W2102434872 countsByYear W21024348722023 @default.
• W2102434872 crossrefType "journal-article" @default.
• W2102434872 hasAuthorship W2102434872A5020619230 @default.
• W2102434872 hasAuthorship W2102434872A5025232222 @default.
• W2102434872 hasAuthorship W2102434872A5033761148 @default.
• W2102434872 hasAuthorship W2102434872A5046026391 @default.
• W2102434872 hasAuthorship W2102434872A5052831097 @default.
• W2102434872 hasAuthorship W2102434872A5059275010 @default.
• W2102434872 hasAuthorship W2102434872A5061617505 @default.
• W2102434872 hasAuthorship W2102434872A5063153590 @default.
• W2102434872 hasAuthorship W2102434872A5063690344 @default.
• W2102434872 hasAuthorship W2102434872A5068735853 @default.
• W2102434872 hasAuthorship W2102434872A5076933919 @default.
• W2102434872 hasAuthorship W2102434872A5088311959 @default.
• W2102434872 hasBestOaLocation W21024348721 @default.
• W2102434872 hasConcept C105795698 @default.
• W2102434872 hasConcept C106131492 @default.
• W2102434872 hasConcept C111919701 @default.
• W2102434872 hasConcept C11413529 @default.
• W2102434872 hasConcept C124101348 @default.
• W2102434872 hasConcept C126255220 @default.
• W2102434872 hasConcept C127413603 @default.
• W2102434872 hasConcept C140779682 @default.
• W2102434872 hasConcept C167928553 @default.
• W2102434872 hasConcept C19499675 @default.
• W2102434872 hasConcept C199360897 @default.
• W2102434872 hasConcept C20820323 @default.
• W2102434872 hasConcept C21200559 @default.
• W2102434872 hasConcept C24326235 @default.
• W2102434872 hasConcept C2777904410 @default.
• W2102434872 hasConcept C31972630 @default.
• W2102434872 hasConcept C33923547 @default.
• W2102434872 hasConcept C41008148 @default.
• W2102434872 hasConcept C55037315 @default.
• W2102434872 hasConcept C76969082 @default.

• next