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System and method for parameter estimation in biological processes

A biological process and parameter technology, applied in biochemical equipment and methods, biostatistics, microbial measurement/inspection, etc., can solve the problem that methylation measurement results do not have normal distribution or Gaussian distribution errors, etc.

Inactive Publication Date: 2013-05-01
AUCKLAND UNISERVICES LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] Methylation measurements may not have normally or Gaussian distributed errors

Method used

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  • System and method for parameter estimation in biological processes
  • System and method for parameter estimation in biological processes
  • System and method for parameter estimation in biological processes

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0069] To illustrate the application of the theory presented above, more than 40 samples were randomly drawn from the 1440 deviations measured by repeated measurements of the same tissues described above. A constant value of 0.55 was added to 20 samples and assigned treatment H, while a constant value of 0.45 was added to the other 20 samples and assigned treatment L. A uniform random variable sampled between 0 and 0.1 is added to each value to simulate inter-individual variation.

[0070] Analysis of variance was performed on this simulated data set using the maximum likelihood method derived above and the state-of-the-art least squares technique. The least squares estimates were not significantly different (P<0.22), with estimates of H=0.55±0.10 and L=0.46±0.10. However, the maximum likelihood estimate was highly significant (P<0.01), with estimates of H=0.55±0.04 and L=0.45±0.04.

[0071] Since this simulation example has a difference between the H and L performed specifi...

Embodiment 2

[0072] Example 2: Application of Estimating the Effect of Parity on the Promoter Methylation of the H19 Gene

[0073] The ratio of CpG methylation at 13 CpG sites in the promoter of the H19 gene measured on the subjects' marrow samples described in the Materials and Methods section was analyzed to determine parity by means of maximum likelihood using the method described above sexual influence.

[0074] The frequency distribution of methylation measurements at each CpG site showed a high degree of non-normality, all with skewed tails, with high bias at low frequencies. figure 2 An example of CpG(2) is shown in . In these cases the "usual" ANOVA least squares procedure would be expected to perform poorly, and the inferences would be unreliable. Taking a logarithmic transformation did not improve the situation, probably because the form of the tail of the methylation distribution falls faster than the exponential form.

[0075] The effect of parity on the estimates of the pr...

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Abstract

A method of measuring a biological process, the method including the steps of: (a) determining a probability density function for a series of repeated measurements of the biological process; (b) approximating the probability density function utilising a parametric formula; (c) determining a maximum likelihood estimator for the parametric formulation of the probability density function; and (d) utilising the maximum likelihood estimator for subsequent measurements of the biological process.

Description

field of invention [0001] The present invention relates to parameter estimation of biological processes and in particular discloses methods for more accurately measuring biological processes such as CpG methylation or similar biological processes. Background of the invention [0002] In the accurate measurement of biological processes, errors arise from the approximation and imprecise recording of measured values. Various techniques have been developed to minimize or reduce the effects of errors in measurements. A popular technique is the "least squares" method, which is often used to fit measured data to a predetermined model. If properly inferred, the method of least squares relies on the key assumption of a normal or Gaussian frequency distribution. In cases where the underlying distribution is nonnormal, parameter estimates may be invalid and the resulting inferences misleading. So using least squares in such cases may lead to incorrect results. [0003] For example,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F19/12C12Q1/68G16B40/00
CPCG06F19/24G16B40/00
Inventor 安东尼·布莱恩·普莱曾茨卡梅伦·安格斯·麦克莱因格雷姆·查尔斯·韦克艾伦·迈克尔·谢泼德皮特·大卫·格卢克曼
Owner AUCKLAND UNISERVICES LTD