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NPMLE in estimating the number of ex...

Wang, Jiping.

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NPMLE in estimating the number of expressed genes using EST data while accounting for measurement error.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	NPMLE in estimating the number of expressed genes using EST data while accounting for measurement error./
作者:	Wang, Jiping.
面頁冊數:	152 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4446.
Contained By:	Dissertation Abstracts International64-09B.
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3106341
ISBN:	0496539070

NPMLE in estimating the number of expressed genes using EST data while accounting for measurement error.
Wang, Jiping.

NPMLE in estimating the number of expressed genes using EST data while accounting for measurement error. - 152 p.

Source: Dissertation Abstracts International, Volume: 64-09, Section: B, page: 4446.

Thesis (Ph.D.)--The Pennsylvania State University, 2003.

A cDNA library can be regarded as a population of transcripts with the size of millions, from N distinct expressed gene species. Each individual in this library is called a cDNA clone uniquely derived from an mRNA transcript. cDNA clones are ran

ISBN: 0496539070Subjects--Topical Terms:

517247
Statistics.

NPMLE in estimating the number of expressed genes using EST data while accounting for measurement error.
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520 $a A cDNA library can be regarded as a population of transcripts with the size of millions, from N distinct expressed gene species. Each individual in this library is called a cDNA clone uniquely derived from an mRNA transcript. cDNA clones are ran
520 $a The first part of the thesis deals with measurement error problem. EST clustering is a critical step in generating the data needed for statistical modeling. The accuracy of the statistical data is determined by various types of errors. In this t
520 $a Estimating the number of expressed genes N is a version of the species number estimation problem. We build a Poisson mixture model and develop three variants of the nonparametric maximum likelihood estimator for the estimation of N. These varian
590 $a School code: 0176.
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