Computational Methods for the Analysis of Chemical Sensor Array Data from Volatile Analytes

Jurs, Peter C.; Bakken, Gregory A.; McClelland, Heidi Engelhardt

doi:10.1021/cr9800964

Cited by 593 publications

(554 citation statements)

References 140 publications

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“…This may be particularly relevant for natural olfactory systems as well as artificial noses [16,17]. In such systems, different types of olfactory receptor neurons or chemical sensors detect different spectra of compounds.…”

Section: Discussionmentioning

confidence: 99%

Pattern orthogonalization via channel decorrelation by adaptive networks

et al. 2009

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The early processing of sensory information by neuronal circuits often includes a reshaping of activity patterns that may facilitate the further processing of stimulus representations in the brain. Motivated by recent studies in the olfactory system we study simple adaptive networks that aim to orthogonalize activity patterns representing similar stimuli. Biologically it is plausible that the adaptation is driven by simultaneous correlations between the input channels rather than by the similarity of input patterns that the animal experiences at different times. We demonstrate that networks can achieve effective pattern orthogonalization through channel decorrelation if they also equalize their output levels. In feedforward networks adaptation fails for even moderately similar input patterns. Recurrent networks do not have that limitation. When optimized for linear neural dynamics, they can orthogonalize the representations of highly similar input patterns quite well, even if a threshold-linear nonlinearity is retained in the neural dynamics. For complex stimulus ensembles the rectifying neural dynamics can degrade the network performance significantly. Our results provide insights into fundamental features of simplified inhibitory networks that may be relevant for pattern orthogonalization by neuronal circuits.

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Section: Discussionmentioning

confidence: 99%

Pattern orthogonalization via channel decorrelation by adaptive networks

et al. 2009

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“…4. The raw data obtained were subjected to Linear Discriminant Analysis (LDA) (40,41) to maximize the ratio between-class variance to the within-class variance, thus differentiate the fluorescence response patterns of the NP-PPECO2 system the cell targets. This analysis reduced the size of the training matrix and transformed them into canonical factors that are linear combination of the fluorescence response patterns (i) 2 factors ϫ 6 replicates ϫ 4 cell, (ii) 2 factors ϫ 6 replicates ϫ 3 cells, and (iii) 2 factors ϫ 6 replicates ϫ 3 cells, respectively.…”

Section: Methodsmentioning

confidence: 99%

Detection and differentiation of normal, cancerous, and metastatic cells using nanoparticle-polymer sensor arrays

Bajaj¹,

Miranda²,

Kim

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

285

255

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Rapid and effective differentiation between normal and cancer cells is an important challenge for the diagnosis and treatment of tumors. Here, we describe an array-based system for identification of normal and cancer cells based on a ''chemical nose/tongue'' approach that exploits subtle changes in the physicochemical nature of different cell surfaces. Their differential interactions with functionalized nanoparticles are transduced through displacement of a multivalent polymer fluorophore that is quenched when bound to the particle and fluorescent after release. Using this sensing strategy we can rapidly (minutes/seconds) and effectively distinguish (i) different cell types; (ii) normal, cancerous and metastatic human breast cells; and (iii) isogenic normal, cancerous and metastatic murine epithelial cell lines.fluorescence ͉ gold nanoparticle ͉ sensor ͉ conjugated polymer

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“…Ïðè äàëüíåéøåì çàïîëíåíèè òàáëèöû äàííûìè íîâûõ îáðàçöîâ ÷èñëî êëàñòåðîâ, î÷åâèäíî, áó-äåò ñòðåìèòüñÿ ê íåêîé îïòèìàëüíîé âåëè÷èíå. Â íàøåì ñëó÷àå, îäíàêî, áîëåå íàãëÿäíîé îêàçàëàñü êëàññèôèêàöèÿ ïîëó÷åííûõ äàí-íûõ ìåòîäîì àíàëèçà ãëàâíûõ êîìïîíåíò [13]. Èñïîëüçîâàíèå ýòîãî ìåòîäà ïîçâîëÿåò ïîíèçèòü ðàçìåðíîñòü èñõîäíîé òðåõìåðíîé áàçû äàííûõ äî äâóõ ãëàâíûõ êîìïîíåíò (ÃÊ), è òîãäà êàae-äîå îòäåëüíîå íàáëþäåíèå ïðåäñòàâëÿåòñÿ òî÷-êîé íà ïëîñêîñòè â ïðÿìîóãîëüíîé ñèñòåìå êî-îðäèíàò ÃÊ1 è ÃÊ2.…”

Section: àíàëèç ïîëó÷åííûõ äàííûõunclassified

A method for express estimation of the octane number of gasoline using a portable spectroimpedance meter and statistical analysis methods

et al. 2017

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The authors propose a method for determination of the electro-physical characteristics of electrical insulating liquids on the example of different types of gasoline. The method is based on the spectral impedance measurements of a capacitor electrochemical cell filled with the liquid under study. The application of sinusoidal test voltage in the frequency range of 0,1—10 Hz provides more accurate measurements in comparison with known traditional methods. A portable device for measuring total electrical resistance (impedance) of dielectric liquids was designed and constructed. An approach for express estimation of octane number of automobile gasoline using spectroimpedance measurements and statistical multi variation methods of data analysis has been proposed and tested.

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Computational Methods for the Analysis of Chemical Sensor Array Data from Volatile Analytes

Cited by 593 publications

References 140 publications

Pattern orthogonalization via channel decorrelation by adaptive networks

Pattern orthogonalization via channel decorrelation by adaptive networks

Detection and differentiation of normal, cancerous, and metastatic cells using nanoparticle-polymer sensor arrays

A method for express estimation of the octane number of gasoline using a portable spectroimpedance meter and statistical analysis methods

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