FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2896879710> ?p ?o ?g. }

• W2896879710 abstract "Adherent cells exert traction forces on to their environment, which allows them to migrate, to maintain tissue integrity, and to form complex multicellular structures. This traction can be measured in a perturbation-free manner with traction force microscopy (TFM). In TFM, traction is usually calculated via the solution of a linear system, which is complicated by undersampled input data, acquisition noise, and large condition numbers for some methods. Therefore, standard TFM algorithms either employ data filtering or regularization. However, these approaches require a manual selection of filter- or regularization parameters and consequently exhibit a substantial degree of subjectiveness. This shortcoming is particularly serious when cells in different conditions are to be compared because optimal noise suppression needs to be adapted for every situation, which invariably results in systematic errors. Here, we systematically test the performance of new methods from computer vision and Bayesian inference for solving the inverse problem in TFM. We compare two classical schemes, L1- and L2-regularization, with three previously untested schemes, namely Elastic Net regularization, Proximal Gradient Lasso, and Proximal Gradient Elastic Net. Overall, we find that Elastic Net regularization, which combines L1 and L2 regularization, outperforms all other methods with regard to accuracy of traction reconstruction. Next, we develop two methods, Bayesian L2 regularization and Advanced Bayesian L2 regularization, for automatic, optimal L2 regularization. Using artificial data and experimental data, we show that these methods enable robust reconstruction of traction without requiring a difficult selection of regularization parameters specifically for each data set. Thus, Bayesian methods can mitigate the considerable uncertainty inherent in comparing cellular traction forces." @default.
• W2896879710 created "2018-10-26" @default.
• W2896879710 creator A5006178896 @default.
• W2896879710 creator A5015521956 @default.
• W2896879710 creator A5038310047 @default.
• W2896879710 creator A5040202845 @default.
• W2896879710 creator A5063430008 @default.
• W2896879710 creator A5063835013 @default.
• W2896879710 creator A5072960998 @default.
• W2896879710 creator A5077517489 @default.
• W2896879710 date "2018-10-13" @default.
• W2896879710 modified "2023-09-26" @default.
• W2896879710 title "Traction force microscopy with optimized regularization and automated Bayesian parameter selection for comparing cells" @default.
• W2896879710 cites W1175808865 @default.
• W2896879710 cites W1588835142 @default.
• W2896879710 cites W1648445109 @default.
• W2896879710 cites W1774737416 @default.
• W2896879710 cites W1886579186 @default.
• W2896879710 cites W1895520453 @default.
• W2896879710 cites W191129667 @default.
• W2896879710 cites W1965933207 @default.
• W2896879710 cites W1975449371 @default.
• W2896879710 cites W1994076220 @default.
• W2896879710 cites W1998762105 @default.
• W2896879710 cites W2013352441 @default.
• W2896879710 cites W2017536526 @default.
• W2896879710 cites W2032780005 @default.
• W2896879710 cites W2035382078 @default.
• W2896879710 cites W2035393702 @default.
• W2896879710 cites W2060065908 @default.
• W2896879710 cites W2064883155 @default.
• W2896879710 cites W2070127246 @default.
• W2896879710 cites W2086244192 @default.
• W2896879710 cites W2089455430 @default.
• W2896879710 cites W2096769905 @default.
• W2896879710 cites W2111412288 @default.
• W2896879710 cites W2112820452 @default.
• W2896879710 cites W2113642685 @default.
• W2896879710 cites W2121091193 @default.
• W2896879710 cites W2121492835 @default.
• W2896879710 cites W2122825543 @default.
• W2896879710 cites W2127175247 @default.
• W2896879710 cites W2135046866 @default.
• W2896879710 cites W2135165925 @default.
• W2896879710 cites W2136870306 @default.
• W2896879710 cites W2137968665 @default.
• W2896879710 cites W2145096794 @default.
• W2896879710 cites W2149726258 @default.
• W2896879710 cites W2149846618 @default.
• W2896879710 cites W2158940042 @default.
• W2896879710 cites W2169047326 @default.
• W2896879710 cites W2286195402 @default.
• W2896879710 cites W2290963622 @default.
• W2896879710 cites W2293825098 @default.
• W2896879710 cites W2345307871 @default.
• W2896879710 cites W2432864486 @default.
• W2896879710 cites W2523099503 @default.
• W2896879710 cites W2527346986 @default.
• W2896879710 cites W2675059502 @default.
• W2896879710 cites W2742286879 @default.
• W2896879710 cites W2755607735 @default.
• W2896879710 cites W2762450632 @default.
• W2896879710 cites W2799561730 @default.
• W2896879710 cites W2911546748 @default.
• W2896879710 cites W2913535645 @default.
• W2896879710 cites W2952975724 @default.
• W2896879710 cites W3106160981 @default.
• W2896879710 cites W413440677 @default.
• W2896879710 doi "https://doi.org/10.48550/arxiv.1810.05848" @default.
• W2896879710 hasPublicationYear "2018" @default.
• W2896879710 type Work @default.
• W2896879710 sameAs 2896879710 @default.
• W2896879710 citedByCount "0" @default.
• W2896879710 crossrefType "posted-content" @default.
• W2896879710 hasAuthorship W2896879710A5006178896 @default.
• W2896879710 hasAuthorship W2896879710A5015521956 @default.
• W2896879710 hasAuthorship W2896879710A5038310047 @default.
• W2896879710 hasAuthorship W2896879710A5040202845 @default.
• W2896879710 hasAuthorship W2896879710A5063430008 @default.
• W2896879710 hasAuthorship W2896879710A5063835013 @default.
• W2896879710 hasAuthorship W2896879710A5072960998 @default.
• W2896879710 hasAuthorship W2896879710A5077517489 @default.
• W2896879710 hasBestOaLocation W28968797101 @default.
• W2896879710 hasConcept C107673813 @default.
• W2896879710 hasConcept C11413529 @default.
• W2896879710 hasConcept C126255220 @default.
• W2896879710 hasConcept C127413603 @default.
• W2896879710 hasConcept C134306372 @default.
• W2896879710 hasConcept C135252773 @default.
• W2896879710 hasConcept C141718189 @default.
• W2896879710 hasConcept C148483581 @default.
• W2896879710 hasConcept C152442038 @default.
• W2896879710 hasConcept C154945302 @default.
• W2896879710 hasConcept C203868755 @default.
• W2896879710 hasConcept C2776135515 @default.
• W2896879710 hasConcept C2776214188 @default.
• W2896879710 hasConcept C33923547 @default.
• W2896879710 hasConcept C38834483 @default.
• W2896879710 hasConcept C41008148 @default.
• W2896879710 hasConcept C78519656 @default.

• next