Generalized centroid estimators in bioinformatics.

In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of...

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Autores principales:	Michiaki Hamada, Hisanori Kiryu, Wataru Iwasaki, Kiyoshi Asai
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/500da4ec405c4e1bb36ef8395e661464
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spelling	oai:doaj.org-article:500da4ec405c4e1bb36ef8395e6614642021-11-18T06:58:30ZGeneralized centroid estimators in bioinformatics.1932-620310.1371/journal.pone.0016450https://doaj.org/article/500da4ec405c4e1bb36ef8395e6614642011-02-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21365017/?tool=EBIhttps://doaj.org/toc/1932-6203In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics.Michiaki HamadaHisanori KiryuWataru IwasakiKiyoshi AsaiPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 2, p e16450 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Michiaki Hamada Hisanori Kiryu Wataru Iwasaki Kiyoshi Asai Generalized centroid estimators in bioinformatics.
description	In a number of estimation problems in bioinformatics, accuracy measures of the target problem are usually given, and it is important to design estimators that are suitable to those accuracy measures. However, there is often a discrepancy between an employed estimator and a given accuracy measure of the problem. In this study, we introduce a general class of efficient estimators for estimation problems on high-dimensional binary spaces, which represent many fundamental problems in bioinformatics. Theoretical analysis reveals that the proposed estimators generally fit with commonly-used accuracy measures (e.g. sensitivity, PPV, MCC and F-score) as well as it can be computed efficiently in many cases, and cover a wide range of problems in bioinformatics from the viewpoint of the principle of maximum expected accuracy (MEA). It is also shown that some important algorithms in bioinformatics can be interpreted in a unified manner. Not only the concept presented in this paper gives a useful framework to design MEA-based estimators but also it is highly extendable and sheds new light on many problems in bioinformatics.
format	article
author	Michiaki Hamada Hisanori Kiryu Wataru Iwasaki Kiyoshi Asai
author_facet	Michiaki Hamada Hisanori Kiryu Wataru Iwasaki Kiyoshi Asai
author_sort	Michiaki Hamada
title	Generalized centroid estimators in bioinformatics.
title_short	Generalized centroid estimators in bioinformatics.
title_full	Generalized centroid estimators in bioinformatics.
title_fullStr	Generalized centroid estimators in bioinformatics.
title_full_unstemmed	Generalized centroid estimators in bioinformatics.
title_sort	generalized centroid estimators in bioinformatics.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/500da4ec405c4e1bb36ef8395e661464
work_keys_str_mv	AT michiakihamada generalizedcentroidestimatorsinbioinformatics AT hisanorikiryu generalizedcentroidestimatorsinbioinformatics AT wataruiwasaki generalizedcentroidestimatorsinbioinformatics AT kiyoshiasai generalizedcentroidestimatorsinbioinformatics
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Generalized centroid estimators in bioinformatics.

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