Matches in SemOpenAlex for { <https://semopenalex.org/work/W4233652778> ?p ?o ?g. }
Showing items 1 to 71 of
71
with 100 items per page.
- W4233652778 abstract "<a>Dealing with a system of first-order reactions is a recurrent problem in chemometrics, especially in the analysis of data obtained by spectroscopic methods. Here we argue that global multiexponential fitting, the still common way to solve this kind of problems has serious weaknesses, in contrast to the available contemporary methods of sparse modeling. Combining the advantages of group-lasso and elastic net – the statistical methods proven to be very powerful in other areas – we obtained an optimization problem tunable to result in from very sparse to very dense distribution over a large pre-defined grid of time constants, fitting both simulated and experimental multiwavelength spectroscopic data with very high performance. Moreover, it was found that the optimal values of the tuning hyperparameters can be selected by a machine-learning algorithm based on a Bayesian optimization procedure, utilizing a widely used and a novel version of cross-validation. The applied algorithm recovered very exactly the true sparse kinetic parameters of an extremely complex simulated model of the bacteriorhodopsin photocycle, as well as the wide peak of hypothetical distributed kinetics in the presence of different levels of noise. It also performed well in the analysis of the ultrafast experimental fluorescence kinetics data detected on the coenzyme FAD in a very wide logarithmic time window.</a>" @default.
- W4233652778 created "2022-05-12" @default.
- W4233652778 creator A5001476488 @default.
- W4233652778 creator A5014163868 @default.
- W4233652778 creator A5067500441 @default.
- W4233652778 creator A5077975696 @default.
- W4233652778 creator A5088077225 @default.
- W4233652778 date "2020-12-24" @default.
- W4233652778 modified "2023-09-29" @default.
- W4233652778 title "Machine Learning-Based Model Selection and Parameter Estimation from Kinetic Data of Complex First-Order Reaction Systems" @default.
- W4233652778 doi "https://doi.org/10.26434/chemrxiv.13483335" @default.
- W4233652778 hasPublicationYear "2020" @default.
- W4233652778 type Work @default.
- W4233652778 citedByCount "0" @default.
- W4233652778 crossrefType "posted-content" @default.
- W4233652778 hasAuthorship W4233652778A5001476488 @default.
- W4233652778 hasAuthorship W4233652778A5014163868 @default.
- W4233652778 hasAuthorship W4233652778A5067500441 @default.
- W4233652778 hasAuthorship W4233652778A5077975696 @default.
- W4233652778 hasAuthorship W4233652778A5088077225 @default.
- W4233652778 hasBestOaLocation W42336527781 @default.
- W4233652778 hasConcept C10485038 @default.
- W4233652778 hasConcept C105795698 @default.
- W4233652778 hasConcept C11413529 @default.
- W4233652778 hasConcept C119857082 @default.
- W4233652778 hasConcept C12267149 @default.
- W4233652778 hasConcept C136764020 @default.
- W4233652778 hasConcept C151304367 @default.
- W4233652778 hasConcept C154945302 @default.
- W4233652778 hasConcept C185429906 @default.
- W4233652778 hasConcept C186060115 @default.
- W4233652778 hasConcept C2778049539 @default.
- W4233652778 hasConcept C33923547 @default.
- W4233652778 hasConcept C37616216 @default.
- W4233652778 hasConcept C41008148 @default.
- W4233652778 hasConcept C8642999 @default.
- W4233652778 hasConcept C86803240 @default.
- W4233652778 hasConcept C93959086 @default.
- W4233652778 hasConceptScore W4233652778C10485038 @default.
- W4233652778 hasConceptScore W4233652778C105795698 @default.
- W4233652778 hasConceptScore W4233652778C11413529 @default.
- W4233652778 hasConceptScore W4233652778C119857082 @default.
- W4233652778 hasConceptScore W4233652778C12267149 @default.
- W4233652778 hasConceptScore W4233652778C136764020 @default.
- W4233652778 hasConceptScore W4233652778C151304367 @default.
- W4233652778 hasConceptScore W4233652778C154945302 @default.
- W4233652778 hasConceptScore W4233652778C185429906 @default.
- W4233652778 hasConceptScore W4233652778C186060115 @default.
- W4233652778 hasConceptScore W4233652778C2778049539 @default.
- W4233652778 hasConceptScore W4233652778C33923547 @default.
- W4233652778 hasConceptScore W4233652778C37616216 @default.
- W4233652778 hasConceptScore W4233652778C41008148 @default.
- W4233652778 hasConceptScore W4233652778C8642999 @default.
- W4233652778 hasConceptScore W4233652778C86803240 @default.
- W4233652778 hasConceptScore W4233652778C93959086 @default.
- W4233652778 hasLocation W42336527781 @default.
- W4233652778 hasOpenAccess W4233652778 @default.
- W4233652778 hasPrimaryLocation W42336527781 @default.
- W4233652778 hasRelatedWork W11937450 @default.
- W4233652778 hasRelatedWork W12730994 @default.
- W4233652778 hasRelatedWork W14046414 @default.
- W4233652778 hasRelatedWork W3999907 @default.
- W4233652778 hasRelatedWork W4209967 @default.
- W4233652778 hasRelatedWork W5116624 @default.
- W4233652778 hasRelatedWork W8208283 @default.
- W4233652778 hasRelatedWork W8452303 @default.
- W4233652778 hasRelatedWork W9580097 @default.
- W4233652778 hasRelatedWork W13460795 @default.
- W4233652778 isParatext "false" @default.
- W4233652778 isRetracted "false" @default.
- W4233652778 workType "article" @default.