FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2952476229> ?p ?o ?g. }

• W2952476229 abstract "Abstract Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present la rge- s cale si mulation m odeling (LASSIM), which is the first general mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE) for gene regulatory networks (GRNs). LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady states and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. LASSIM models are built in two steps, where each step can integrate multiple data-types, and the method is implemented as a general-purpose toolbox using the PyGMo Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim . As a method, LASSIM first infers a non-linear ODE system of the pre-specified core genes. Second, LASSIM optimizes the parameters that models the regulation of peripheral genes by core-system genes in parallel. We showed the usefulness of this method by applying LASSIM to infer a large-scale nonlinear model of naïve Th2 differentiation, made possible by integrating Th2 specific bindings, time-series and six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models with truly systems-level data. We exemplified the advantage by inferring the first mechanistically motivated genome-wide model of the Th2 transcription regulatory system, which plays an important role in the progression of immune related diseases. Author summary There are excellent methods to mathematically model time-resolved biological data on a small scale using accurate mechanistic models. Despite the rapidly increasing availability of such data, mechanistic models have not been applied on a genome-wide level due to excessive runtimes and the non-identifiability of model parameters. However, genome-wide, mechanistic models could potentially answer key clinical questions, such as finding the best drug combinations to induce an expression change from a disease to a healthy state. We present LASSIM, which is a toolbox built to infer parameters within mechanistic models on a genomic scale. This is made possible due to a property shared across biological systems, namely the existence of a subset of master regulators, here denoted the core system. The introduction of a core system of genes simplifies the inference into small solvable subproblems, and implies that all main regulatory actions on peripheral genes come from a small set of regulator genes. This separation allows substantial parts of computations to be solved in parallel, i.e. permitting the use of a computer cluster, which substantially reduces the time required for the computation to finish." @default.
• W2952476229 created "2019-06-27" @default.
• W2952476229 creator A5000753874 @default.
• W2952476229 creator A5008968464 @default.
• W2952476229 creator A5014252689 @default.
• W2952476229 creator A5017289997 @default.
• W2952476229 creator A5019017859 @default.
• W2952476229 creator A5024120345 @default.
• W2952476229 creator A5039574191 @default.
• W2952476229 creator A5041150403 @default.
• W2952476229 creator A5049087148 @default.
• W2952476229 creator A5049770857 @default.
• W2952476229 creator A5050648584 @default.
• W2952476229 creator A5072220778 @default.
• W2952476229 creator A5083579373 @default.
• W2952476229 creator A5083934419 @default.
• W2952476229 creator A5084550031 @default.
• W2952476229 creator A5088570894 @default.
• W2952476229 date "2017-03-09" @default.
• W2952476229 modified "2023-09-27" @default.
• W2952476229 title "LASSIM - a network inference toolbox for genome-wide mechanistic modeling" @default.
• W2952476229 cites W1501949263 @default.
• W2952476229 cites W1577053917 @default.
• W2952476229 cites W1893022572 @default.
• W2952476229 cites W1900337607 @default.
• W2952476229 cites W1939125543 @default.
• W2952476229 cites W1973603971 @default.
• W2952476229 cites W1978394237 @default.
• W2952476229 cites W1978486653 @default.
• W2952476229 cites W1979181404 @default.
• W2952476229 cites W1991330182 @default.
• W2952476229 cites W1992223383 @default.
• W2952476229 cites W1998757083 @default.
• W2952476229 cites W2000233729 @default.
• W2952476229 cites W2010645400 @default.
• W2952476229 cites W2015280752 @default.
• W2952476229 cites W2029946148 @default.
• W2952476229 cites W2040097887 @default.
• W2952476229 cites W2055082742 @default.
• W2952476229 cites W2058221907 @default.
• W2952476229 cites W2065121736 @default.
• W2952476229 cites W2071019594 @default.
• W2952476229 cites W2091570353 @default.
• W2952476229 cites W2092091227 @default.
• W2952476229 cites W2096528235 @default.
• W2952476229 cites W2099701546 @default.
• W2952476229 cites W2099786058 @default.
• W2952476229 cites W2102653059 @default.
• W2952476229 cites W2110062742 @default.
• W2952476229 cites W2113446988 @default.
• W2952476229 cites W2114382052 @default.
• W2952476229 cites W2116467413 @default.
• W2952476229 cites W2126551563 @default.
• W2952476229 cites W2129265801 @default.
• W2952476229 cites W2143894094 @default.
• W2952476229 cites W2147235412 @default.
• W2952476229 cites W2151313241 @default.
• W2952476229 cites W2154835728 @default.
• W2952476229 cites W2157121418 @default.
• W2952476229 cites W2161922735 @default.
• W2952476229 cites W2171428576 @default.
• W2952476229 cites W2176034226 @default.
• W2952476229 cites W2215197314 @default.
• W2952476229 cites W2259938310 @default.
• W2952476229 cites W2272703292 @default.
• W2952476229 cites W2280567170 @default.
• W2952476229 cites W2565099035 @default.
• W2952476229 cites W3099289621 @default.
• W2952476229 doi "https://doi.org/10.1101/115477" @default.
• W2952476229 hasPublicationYear "2017" @default.
• W2952476229 type Work @default.
• W2952476229 sameAs 2952476229 @default.
• W2952476229 citedByCount "0" @default.
• W2952476229 crossrefType "posted-content" @default.
• W2952476229 hasAuthorship W2952476229A5000753874 @default.
• W2952476229 hasAuthorship W2952476229A5008968464 @default.
• W2952476229 hasAuthorship W2952476229A5014252689 @default.
• W2952476229 hasAuthorship W2952476229A5017289997 @default.
• W2952476229 hasAuthorship W2952476229A5019017859 @default.
• W2952476229 hasAuthorship W2952476229A5024120345 @default.
• W2952476229 hasAuthorship W2952476229A5039574191 @default.
• W2952476229 hasAuthorship W2952476229A5041150403 @default.
• W2952476229 hasAuthorship W2952476229A5049087148 @default.
• W2952476229 hasAuthorship W2952476229A5049770857 @default.
• W2952476229 hasAuthorship W2952476229A5050648584 @default.
• W2952476229 hasAuthorship W2952476229A5072220778 @default.
• W2952476229 hasAuthorship W2952476229A5083579373 @default.
• W2952476229 hasAuthorship W2952476229A5083934419 @default.
• W2952476229 hasAuthorship W2952476229A5084550031 @default.
• W2952476229 hasAuthorship W2952476229A5088570894 @default.
• W2952476229 hasBestOaLocation W29524762291 @default.
• W2952476229 hasConcept C104317684 @default.
• W2952476229 hasConcept C111919701 @default.
• W2952476229 hasConcept C124101348 @default.
• W2952476229 hasConcept C134306372 @default.
• W2952476229 hasConcept C150194340 @default.
• W2952476229 hasConcept C154945302 @default.
• W2952476229 hasConcept C199360897 @default.
• W2952476229 hasConcept C2776214188 @default.
• W2952476229 hasConcept C2777655017 @default.

• next