Matches in SemOpenAlex for { <https://semopenalex.org/work/W2601195745> ?p ?o ?g. }
Showing items 1 to 95 of
95
with 100 items per page.
- W2601195745 abstract "Abstract —In this paper we investigate the influence of externalnoise on the inference of network structures. The purpose of oursimulations is to gain insights in the experimental design of mi-croarray experiments to infer, e.g., transcription regulatory networksfrom microarray experiments. Here external noise means, that thedynamics of the system under investigation, e.g., temporal changes ofmRNA concentration, is affected by measurement errors. Additionallyto external noise another problem occurs in the context of microarrayexperiments. Practically, it is not possible to monitor the mRNAconcentration over an arbitrary long time period as demanded by thestatistical methods used to learn the underlying network structure. Forthis reason, we use only short time series to make our simulationsmore biologically plausible. Keywords —Dynamic Bayesian networks, structure learning, genenetworks, Markov chain Monte Carlo, microarray data. I. I NTRODUCTION D YNAMIC Bayesian networks are a special example ofgraphicalmodelsthatcombinepropertiesfromgraphandprobability theory [10]. Causally speaking, graphical modelsallow the visualization of multivariate probability distributionswhere nodes in a graph represent random variables andconnections between nodes indicate dependencies betweenthe random variables [1]. In recent years, Bayesian networksand dynamic Bayesian networks, which are an extention ofBayesian networks in the respect that the underlying directedgraph can contain cycles, are used to analyze gene expres-sion data from microarray experiments [4], [13], [6], [8].Especially, dynamic Bayesian networks seems to be a goodchoice for this task, because gene networks, e.g., transcriptionregulatory networks, contain positive and negative feedbackloops as L" @default.
- W2601195745 created "2017-04-07" @default.
- W2601195745 creator A5014560349 @default.
- W2601195745 creator A5021712397 @default.
- W2601195745 creator A5044244385 @default.
- W2601195745 creator A5057625030 @default.
- W2601195745 date "2005-12-01" @default.
- W2601195745 modified "2023-09-26" @default.
- W2601195745 title "Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series" @default.
- W2601195745 cites W1669437150 @default.
- W2601195745 cites W1746680969 @default.
- W2601195745 cites W1896341954 @default.
- W2601195745 cites W2012804055 @default.
- W2601195745 cites W2061280979 @default.
- W2601195745 cites W2069739265 @default.
- W2601195745 cites W2076372398 @default.
- W2601195745 cites W2082982706 @default.
- W2601195745 cites W2095622082 @default.
- W2601195745 cites W2126602684 @default.
- W2601195745 cites W2145068337 @default.
- W2601195745 cites W2159080219 @default.
- W2601195745 cites W2161511352 @default.
- W2601195745 cites W2611370172 @default.
- W2601195745 cites W89551800 @default.
- W2601195745 hasPublicationYear "2005" @default.
- W2601195745 type Work @default.
- W2601195745 sameAs 2601195745 @default.
- W2601195745 citedByCount "2" @default.
- W2601195745 countsByYear W26011957452017 @default.
- W2601195745 crossrefType "journal-article" @default.
- W2601195745 hasAuthorship W2601195745A5014560349 @default.
- W2601195745 hasAuthorship W2601195745A5021712397 @default.
- W2601195745 hasAuthorship W2601195745A5044244385 @default.
- W2601195745 hasAuthorship W2601195745A5057625030 @default.
- W2601195745 hasConcept C107673813 @default.
- W2601195745 hasConcept C111350023 @default.
- W2601195745 hasConcept C119857082 @default.
- W2601195745 hasConcept C124101348 @default.
- W2601195745 hasConcept C151406439 @default.
- W2601195745 hasConcept C151730666 @default.
- W2601195745 hasConcept C154945302 @default.
- W2601195745 hasConcept C155846161 @default.
- W2601195745 hasConcept C160234255 @default.
- W2601195745 hasConcept C169272836 @default.
- W2601195745 hasConcept C2776214188 @default.
- W2601195745 hasConcept C2779343474 @default.
- W2601195745 hasConcept C33724603 @default.
- W2601195745 hasConcept C41008148 @default.
- W2601195745 hasConcept C71983512 @default.
- W2601195745 hasConcept C82142266 @default.
- W2601195745 hasConcept C86803240 @default.
- W2601195745 hasConceptScore W2601195745C107673813 @default.
- W2601195745 hasConceptScore W2601195745C111350023 @default.
- W2601195745 hasConceptScore W2601195745C119857082 @default.
- W2601195745 hasConceptScore W2601195745C124101348 @default.
- W2601195745 hasConceptScore W2601195745C151406439 @default.
- W2601195745 hasConceptScore W2601195745C151730666 @default.
- W2601195745 hasConceptScore W2601195745C154945302 @default.
- W2601195745 hasConceptScore W2601195745C155846161 @default.
- W2601195745 hasConceptScore W2601195745C160234255 @default.
- W2601195745 hasConceptScore W2601195745C169272836 @default.
- W2601195745 hasConceptScore W2601195745C2776214188 @default.
- W2601195745 hasConceptScore W2601195745C2779343474 @default.
- W2601195745 hasConceptScore W2601195745C33724603 @default.
- W2601195745 hasConceptScore W2601195745C41008148 @default.
- W2601195745 hasConceptScore W2601195745C71983512 @default.
- W2601195745 hasConceptScore W2601195745C82142266 @default.
- W2601195745 hasConceptScore W2601195745C86803240 @default.
- W2601195745 hasLocation W26011957451 @default.
- W2601195745 hasOpenAccess W2601195745 @default.
- W2601195745 hasPrimaryLocation W26011957451 @default.
- W2601195745 hasRelatedWork W1480555899 @default.
- W2601195745 hasRelatedWork W1531406273 @default.
- W2601195745 hasRelatedWork W1971067275 @default.
- W2601195745 hasRelatedWork W1987597996 @default.
- W2601195745 hasRelatedWork W1988418558 @default.
- W2601195745 hasRelatedWork W2017748100 @default.
- W2601195745 hasRelatedWork W2105130030 @default.
- W2601195745 hasRelatedWork W2140952948 @default.
- W2601195745 hasRelatedWork W2375080634 @default.
- W2601195745 hasRelatedWork W2951176680 @default.
- W2601195745 hasRelatedWork W2962859852 @default.
- W2601195745 hasRelatedWork W2978366427 @default.
- W2601195745 hasRelatedWork W2986084690 @default.
- W2601195745 hasRelatedWork W3038180796 @default.
- W2601195745 hasRelatedWork W3092637396 @default.
- W2601195745 hasRelatedWork W3103770455 @default.
- W2601195745 hasRelatedWork W3122298409 @default.
- W2601195745 hasRelatedWork W3130269981 @default.
- W2601195745 hasRelatedWork W3145888521 @default.
- W2601195745 hasRelatedWork W3165008622 @default.
- W2601195745 isParatext "false" @default.
- W2601195745 isRetracted "false" @default.
- W2601195745 magId "2601195745" @default.
- W2601195745 workType "article" @default.