Expert system for data acquisition to achieve a constant signal-to-noise ratio:  application to imaging of DNA sequencing gels

Koutny, Lance; Yeung, Edward S.

doi:10.1021/ac00050a010

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…When a computer program utilizes computational techniques that try to simulate human reasoning to solve complex problems, it is called an expert system. With the advent of fast, powerful, and inexpensive computers in the last decades, many applications of expert systems to solve specific problems have appeared in various research fields (Zhang and Chait, 2000;Koutny and Yeung, 1993;Harrington et al, 1989).…”

Section: Expert System For the Classificationmentioning

confidence: 99%

Characterization of Individual Atmospheric Aerosols Using Quantitative Energy Dispersive-Electron Probe X-ray Microanalysis: A Review

Kim¹,

Ro²

2010

ajae

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Great concerns about atmospheric aerosols are attributed to their multiple roles to atmospheric processes. For example, atmospheric aerosols influence global climate, directly by scattering or absorbing solar radiations and indirectly by serving as cloud condensation nuclei. They also have a significant impact on human health and visibility. Many of these effects depend on the size and composition of atmospheric aerosols, and thus detailed information on the physicochemical properties and the distribution of airborne particles is critical to accurately predict their impact on the Earth's climate as well as human health. A single particle analysis technique, named low-Z particle electron probe X-ray microanalysis (low-Z particle EPMA) that can determine the concentration of low-Z elements such as carbon, nitrogen and oxygen in a microscopic volume has been developed. The capability of quantitative analysis of low-Z elements in individual particle allows the characterization of especially important atmospheric particles such as sulfates, nitrates, ammonium, and carbonaceous particles. Furthermore, the diversity and the complicated heterogeneity of atmospheric particles in chemical compositions can be investigated in detail. In this review, the development and methodology of low-Z particle EPMA for the analysis of atmospheric aerosols are introduced. Also, its typical applications for the characterization of various atmospheric particles, i.e., on the chemical compositions, morphologies, the size segregated distributions, and the origins of Asian dust, urban aerosols, indoor aerosols in underground subway station, and Arctic aerosols, are illustrated.

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Section: Expert System For the Classificationmentioning

confidence: 99%

Characterization of Individual Atmospheric Aerosols Using Quantitative Energy Dispersive-Electron Probe X-ray Microanalysis: A Review

Kim¹,

Ro²

2010

ajae

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“…When a program utilizes the computational techniques that try to simulate human reasoning to solve complex problems, it is called an expert system. With the advent of fast, powerful, and inexpensive computers in the past decades, many applications of expert systems to solve specific problems have appeared in various research fields. − Our expert system tries to mimic the logic used by experts in order to determine chemical species of individual particles using the low- Z particle EPMA data. The expert system is implemented by macroprogramming that is done by using the MS Visual Basic interpreter available in MS Excel software.…”

Section: Description Of Expert Systemmentioning

confidence: 99%

An Expert System for Chemical Speciation of Individual Particles Using Low-Z Particle Electron Probe X-ray Microanalysis Data

Kim

Grieken

2004

Anal. Chem.

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An electron probe X-ray microanalysis (EPMA) technique, using an energy-dispersive X-ray detector with an ultrathin window, designated a low-Z particle EPMA, has been developed. The low-Z particle EPMA allows the quantitative determination of concentrations of low-Z elements, such as C, N, and O, as well as chemical elements that can be analyzed by conventional energy-dispersive EPMA, in individual particles. Since a data set is usually composed of data for several thousands of particles in order to make environmentally meaningful observations of real atmospheric aerosol samples, the development of a method that fully extracts chemical information contained in the low-Z particle EPMA data is important. An expert system that can rapidly and reliably perform chemical speciation from the low-Z particle EPMA data is presented. This expert system tries to mimic the logic used by experts and is implemented by applying macroprogramming available in MS Excel software. Its feasibility is confirmed by applying the expert system to data for various types of standard particles and a real atmospheric aerosol sample. By applying the expert system, the time necessary for chemical speciation becomes shortened very much and detailed information on particle data can be saved and extracted later if more information is needed for further analysis.

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“…Finally, selective fluorescence labeling of a small number of molecules present in a tiny volume, for example, in a single cell, is cumbersome or even impossible. In this regard, efforts have been made in direct measurement of the UV absorbance or native fluorescence of proteins to eliminate the problems of staining in two-dimensional gel and microchip electrophoresis. − Generally, proteins exhibit an absorption maximum in the UV region around 280 nm, which mainly arises from the absorption of the three aromatic amino acid residues tryptophan, tyrosine, and phenylalanine . Since 99.5% of all human proteins with a mass of more than 10 kDa contain at least one tryptophan or tyrosine residue (phenylalanine shows substantially weaker fluorescence 23 ), native UV fluorescence detection volunteers as an alternative detection technique for proteins .…”

mentioning

confidence: 99%

UV Fluorescence Lifetime Imaging Microscopy: A Label-Free Method for Detection and Quantification of Protein Interactions

et al. 2005

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Due to the ability to detect multiple parameters simultaneously, protein microarrays have found widespread applications from basic biological research to diagnosis of diseases. Generally, readout of protein microarrays is performed by fluorescence detection using either dye-labeled detector antibodies or direct labeling of the target proteins. We developed a method for the label-free detection and quantification of proteins based on time-gated, wide-field, camera-based UV fluorescence lifetime imaging microscopy to gain lifetime information from each pixel of a sensitive CCD camera. The method relies on differences in the native fluorescence lifetime of proteins and takes advantage of binding-induced lifetime changes for the unequivocal detection and quantification of target proteins. Since fitting of the fluorescence decay for every pixel in an image using a classical exponential decay model is time-consuming and unstable at very low fluorescence intensities, we used a new, very robust and fast alternative method to generate UV fluorescence lifetime images by calculating the average lifetime of the decay for each pixel in the image stack using a model-free average decay time algorithm.To validate the method, we demonstrate the detection and quantification of p53 antibodies, a tumor marker in cancer diagnosis. Using tryptophan-containing capture peptides, we achieved a detection sensitivity for monoclonal antibodies down to the picomolar concentration range. The obtained affinity constant, Ka, of (1.4 +/- 0.6) x 10(9) M(-1), represents a typical value for antigen/antibody binding and is in agreement with values determined by traditional binding assays.

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Expert system for data acquisition to achieve a constant signal-to-noise ratio: application to imaging of DNA sequencing gels

Cited by 10 publications

References 14 publications

Characterization of Individual Atmospheric Aerosols Using Quantitative Energy Dispersive-Electron Probe X-ray Microanalysis: A Review

Characterization of Individual Atmospheric Aerosols Using Quantitative Energy Dispersive-Electron Probe X-ray Microanalysis: A Review

An Expert System for Chemical Speciation of Individual Particles Using Low-Z Particle Electron Probe X-ray Microanalysis Data

UV Fluorescence Lifetime Imaging Microscopy: A Label-Free Method for Detection and Quantification of Protein Interactions

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