Mean and variance of ratio estimators used in fluorescence ratio imaging

Kempen, Geert M. P. van; Vliet, Lucas J. van

doi:10.1002/(sici)1097-0320(20000401)39:4<300::aid-cyto8>3.0.co;2-o

Cited by 112 publications

(90 citation statements)

References 3 publications

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“…The third statistic r 3 is a more robust ratio estimate and has been used in the two channel FISH imaging [17]. We have evaluated these metrics in quantifying the gene expression and have shown r 3 is more accurate as will be validated in Section 4.…”

Section: The Third Ratio Estimate R 3 -mentioning

confidence: 97%

“…The most commonly used method is the log intensity ratio, which is obtained from the mean, median or mode of the intensity measurement for each channel. We will introduce two more new statistics [17] when calculating the log intensity ratio in Section 3.5. This new statistic is expected to give a more accurate estimate of gene expression level.…”

Section: Data Quantificationmentioning

confidence: 99%

“…WANG et al Page 8 (17) where is the sample variance of y, and s xy represents the sample covariance of x and y. The last metric provides an asymptotically unbiased estimate of the ratio as E{r 3 } ≈ μ x /μ y [17].…”

Section: The Third Ratio Estimate R 3 -mentioning

confidence: 99%

“…The last metric provides an asymptotically unbiased estimate of the ratio as E{r 3 } ≈ μ x /μ y [17].…”

Section: The Third Ratio Estimate R 3 -mentioning

confidence: 99%

“…The mean background intensities α will be estimated by the proposed algorithms and then the intensities of test and reference signals will be estimated by (22) From this value, the log ratio is calculated using one of the statistics of Eqs. (15)(16)(17). This model was also used in [12].…”

Section: Simulated Data Set-mentioning

confidence: 99%

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A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression

Wang

Gunampally

Chen³

et al. 2007

J Sign Process Syst Sign Image

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Despite the widespread application of microarray imaging for biomedical imaging research, barriers still exist regarding its reliability for clinical use. A critical major problem lies in accurate spot segmentation and the quantification of gene expression level (mRNA) from the microarray images. A variety of commercial and research freeware packages are available, but most cannot handle array spots with complex shapes such as donuts and scratches. Clustering approaches such as k-means and mixture models were introduced to overcome this difficulty, which use the hard labeling of each pixel. In this paper, we apply fuzzy clustering approaches for spot segmentation, which provides soft labeling of the pixel. We compare several fuzzy clustering approaches for microarray analysis and provide a comprehensive study of these approaches for spot segmentation. We show that possiblistic c-means clustering (PCM) provides the best performance in terms of stability criterion when testing on both a variety of simulated and real microarray images. In addition, we compared three statistical criteria in measuring gene expression levels and show that a new asymptotically unbiased statistic is able to quantify the gene expression level more accurately.

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Section: The Third Ratio Estimate R 3 -mentioning

confidence: 97%

Section: Data Quantificationmentioning

confidence: 99%

Section: The Third Ratio Estimate R 3 -mentioning

confidence: 99%

“…The last metric provides an asymptotically unbiased estimate of the ratio as E{r 3 } ≈ μ x /μ y [17].…”

Section: The Third Ratio Estimate R 3 -mentioning

confidence: 99%

Section: Simulated Data Set-mentioning

confidence: 99%

See 3 more Smart Citations

A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression

Wang

Gunampally

Chen³

et al. 2007

J Sign Process Syst Sign Image

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Preclinical pharmacokinetics of a novel HIV‐1 attachment inhibitor BMS‐378806 and prediction of its human pharmacokinetics

Yang

Zadjura

D’Arienzo

et al. 2005

Biopharm & Drug Disp

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BMS-378806 is a prototype of novel HIV attachment inhibitors that block the gp120 and CD4 interaction, the first step of HIV-1 entry into cells. The present work investigated the pharmacokinetics of BMS-378806 in rats, dogs and monkeys and assessed its in vitro permeability and metabolism. BMS-378806 exhibited species-dependent oral bioavailability which was 19%-24% in rats and monkeys and 77% in dogs. In rats and monkeys, absorption was prolonged, with an apparent terminal half-life of 2.1 and 6.5 h, respectively. In rats, linear pharmacokinetics was observed between i.v. doses of 1 and 5 mg/kg and between p.o. doses of 5 and 25 mg/kg. The total body clearance was intermediate in rats and low in dogs and monkeys. The steady-state volume of distribution was moderate (0.4-0.6 l/kg), contributing to a short half-life (0.3-1.2 h) after i.v. dosing. Studies in bile-duct cannulated rats together with intraportal infusion studies revealed that the renal and hepatic clearance each accounted for 30% and 70% of the total elimination in rats, with the hepatic clearance largely being oxidative metabolism. In vitro, BMS-378806 was not highly protein bound (44%-73%). The Caco-2 permeability was modest (51 nm/s) and confounded by P-glycoprotein mediated efflux transport. Both of these may contribute to the low brain penetration observed in rats (brain/plasma AUC ratio=0.06). In human liver microsomes BMS-378806 was equally metabolized by cytochrome P450 1A2, 2D6 and 3A4 and did not inhibit major drug-metabolizing enzymes to a significant extent. Based on in vitro and animal data, a mechanistic approach that factors in absorption and first-pass metabolism was employed to predict the human oral bioavailability of BMS-378806 (ca 20%). This, together with the complex Dedrick plot method, was used to simulate human oral profiles and to project an efficacious dose. These study results offer a comprehensive assessment of the developability of BMS-378806 and provide important guidance to improving absorption and half-life of future compounds in the series. The current studies also demonstrate the value and approaches of understanding pharmacokinetic properties in the early stage of drug discovery.

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Maximum likelihood estimation of FRET efficiency and its implications for distortions in pixelwise calculation of FRET in microscopy

et al. 2014

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Ratiometric determination of the efficiency of fluorescence or F€ orster resonance energy transfer (FRET) is one of the most widespread methods for the characterization of protein clustering and conformation. Low photon numbers, often present in pixel-by-pixel determination of FRET efficiency in digital microscopy, result in large uncertainties in the derived FRET parameter. Here, we propose a method based on maximum likelihood estimation (MLE) of FRET efficiency using photon counting detectors to overcome this limitation. Intensities measured in the donor, FRET, and acceptor channels were all assumed to follow Poisson statistics as a result of detector shot noise. The joint probability of photon numbers detected in the donor, FRET, and acceptor channels was derived using an equation describing the relationship between the three measured intensities. The FRET efficiency generating the measured photon numbers with the largest likelihood was determined iteratively providing a single FRET value for all pixels in the calculation. Since as few as 100 pixels are sufficient to provide a maximum likelihood estimate for FRET, biological variability in FRET values can be revealed by performing the analysis for regions of interests in an image. Since the algorithm provides the probability of a combination of donor, FRET, and acceptor intensities observed in each individual pixel given a certain FRET efficiency, outlier pixels with low probabilities could be excluded from the analysis. Simulations carried out with low photon numbers in the presence and absence of outlier pixels revealed that the proposed approach can reliably and reproducibly estimate FRET efficiency. In addition, systematic evaluation of the simulation results showed that the distribution of pixel-by-pixel FRET efficiencies is skewed, and the mean of these FRET values is a biased and unreliable estimate of the FRET efficiency. In the absence of outlier pixels, FRET calculated from summed donor, FRET, and acceptor intensities proved to be as reliable as MLE. We conclude that MLE of FRET outperforms calculations using summed and pixel-bypixel intensities in biologically relevant situations involving low photon numbers and outlier pixels.

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Mean and variance of ratio estimators used in fluorescence ratio imaging

Cited by 112 publications

References 3 publications

A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression

A Comparison of Fuzzy Clustering Approaches for Quantification of Microarray Gene Expression

Preclinical pharmacokinetics of a novel HIV‐1 attachment inhibitor BMS‐378806 and prediction of its human pharmacokinetics

Maximum likelihood estimation of FRET efficiency and its implications for distortions in pixelwise calculation of FRET in microscopy

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