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Registro Completo |
Biblioteca(s): |
Ebooks. |
Data corrente: |
01/02/2013 |
Data da última atualização: |
01/02/2013 |
Autoria: |
LIN, S.; ZHAO, H. |
Afiliação: |
Shili Lin; Hongyu Zhao. |
Título: |
Handbook on Analyzing Human Genetic Data: Computational Approaches and Software. |
Ano de publicação: |
2010 |
Fonte/Imprenta: |
Springer eBooks. |
Descrição Física: |
digital. |
ISBN: |
9783540692645 |
DOI: |
10.1007/978-3-540-69264-5 |
Idioma: |
Inglês |
Conteúdo: |
Linkage analysis -- Qualitative traits -- Linkage analysis - quantitative traits -- Association studies - population based -- Association studies - family based -- Population genetics -- Haplotype structure -- Haplotype association analysis -- Monte Carlo analysis methods -- Multiple comparison/testing issues -- Disease risk estimation/analysis -- Other resources. .The discipline of statistical genetics is highly computational. Be it exact computational methods, simulation based, or a hybrid of the two, computational packages are indispensable tools and constant companions of researchers in the field. This handbook is intended to provide human geneticists and other biomedical researchers with guidance on selections of appropriate computational methods and software packages for their specific genetic problems. It may also be used by students and other learners as a reference in conjunction with a more theoretical and/or methodologically oriented text book. This book tries to strike a balance between methodological expositions and practical guidelines for software selections. Wherever possible, comparisons among competing methods and software are made to highlight the relative advantages and disadvantage of the approaches so that the readers can make informed choices to best match their specific needs. |
Palavras-Chave: |
Biomedicine; Computational Biology/Bioinformatics; Genetics and Population Dynamics; Mathematical statistics; Statistical Theory and Methods; Statistics for Life Sciences, Medicine, Health Sciences. |
Thesaurus Nal: |
bioinformatics; genetics; human genetics; medicine; statistics. |
Categoria do assunto: |
-- |
URL: |
https://dx.doi.org/10.1007/978-3-540-69264-5
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Marc: |
LEADER 02227nam a2200289 a 4500 001 1947735 005 2013-02-01 008 2010 bl uuuu 00u1 u #d 020 $a9783540692645 024 7 $a10.1007/978-3-540-69264-5$2DOI 100 1 $aLIN, S. 245 $aHandbook on Analyzing Human Genetic Data$bComputational Approaches and Software.$h[electronic resource] 260 $aSpringer eBooks.$c2010 300 $cdigital. 520 $a<P>Linkage analysis -- Qualitative traits -- Linkage analysis - quantitative traits -- Association studies - population based -- Association studies - family based -- Population genetics -- Haplotype structure -- Haplotype association analysis -- Monte Carlo analysis methods -- Multiple comparison/testing issues -- Disease risk estimation/analysis -- Other resources.</P>.<P>The discipline of statistical genetics is highly computational. Be it exact computational methods, simulation based, or a hybrid of the two, computational packages are indispensable tools and constant companions of researchers in the field. This handbook is intended to provide human geneticists and other biomedical researchers with guidance on selections of appropriate computational methods and software packages for their specific genetic problems. It may also be used by students and other learners as a reference in conjunction with a more theoretical and/or methodologically oriented text book. This book tries to strike a balance between methodological expositions and practical guidelines for software selections. Wherever possible, comparisons among competing methods and software are made to highlight the relative advantages and disadvantage of the approaches so that the readers can make informed choices to best match their specific needs.</P> 650 $abioinformatics 650 $agenetics 650 $ahuman genetics 650 $amedicine 650 $astatistics 653 $aBiomedicine 653 $aComputational Biology/Bioinformatics 653 $aGenetics and Population Dynamics 653 $aMathematical statistics 653 $aStatistical Theory and Methods 653 $aStatistics for Life Sciences, Medicine, Health Sciences 700 1 $aZHAO, H.
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1. | | RAHMATI, M.; WEIHERMÜLLER, L.; VANDERBORGHT, J.; PACHEPSKY, Y. A.; MAO, L.; SADEGHI, S. H.; MOOSAVI, N.; KHEIRFAM, H.; MONTZKA, C.; VAN LOOY, K.; TOTH, B.; HAZBAVI, Z.; AL YAMANI, W.; ALBALASMEH, A. A.; ALGHZAWI, M. Z.; ANGULO-JARAMILLO, R.; ANTONINO, A. C. D.; ARAMPATZIS, G.; ARMINDO, R. A.; ASADI, H.; BAMUTAZE, Y.; BATLLE-AGUILAR, J.; BÉCHET, B.; BECKER, F.; BLÖSCHL, G.; BOHNE, K.; BRAUD, I.; CASTELLANO, C.; CERDÀ, A.; CHALHOUB, M.; CICHOTA, R.; CÍSLEROVÁ, M.; CLOTHIER, B.; COQUET, Y.; CORNELIS, W.; CORRADINI, C.; COUTINHO, A. P.; OLIVEIRA, M. B. de; MACEDO, J. R. de; DURÃES, M. F.; EMAMI, H.; ESKANDARI, I.; FARAJNIA, A.; FLAMMINI, A.; FODOR, N.; GHARAIBEH, M.; GHAVIMIPANAH, M. H.; GHEZZEHEI, T. A.; GIERTZ, S.; HATZIGIANNAKIS, E. G.; HORN, R.; JIMÉNEZ, J. J.; JACQUES, D.; KEESSTRA, S. D.; KELISHADI, H.; KIANI-HARCHEGANI, M.; KOUSELOU, M.; KUMAR JHA, M.; LASSABATERE, L.; LI, X.; LIEBIG, M. A.; LICHNER, L.; LÓPEZ, M. V.; MACHIWAL, D.; MALLANTS, D.; MALLMANN, M. S.; MARQUES, J. D. de O.; MARSHALL, M. R.; MERTENS, J.; MEUNIER, F.; MOHAMMADI, M. H.; MOHANTY, B. P.; PULIDO-MONCADA, M.; MONTENEGRO, S.; MORBIDELLI, R.; MORET-FERNÁNDEZ, D.; MOOSAVI, A. A.; MOSADDEGHI, M. R.; MOUSAVI, S. B.; MOZAFFARI, H.; NABIOLLAHI, K.; NEYSHABOURI, M. R.; OTTONI, M. V.; OTTONI FILHO, T. B.; PAHLAVAN-RAD, M. R.; PANAGOPOULOS, A.; PETH, S.; PEYNEAU, P.-E.; PICCIAFUOCO, T.; POESEN, J.; PULIDO, M.; REINERT, D. J.; REINSCH, S.; REZAEI, M.; ROBERTS, F. P.; ROBINSON, D.; RODRIGO-COMINO, J.; ROTUNNO FILHO, O. C.; SAITO, T.; SUGANUMA, H.; SALTALIPPI, C.; SÁNDOR, R.; SCHÜTT, B.; SEEGER, M.; SEPEHRNIA, N.; SHARIFI MOGHADDAM, E.; SHUKLA, M.; SHUTARO, S.; SORANDO, R.; STANLEY, A. A.; STRAUSS, P.; SU, Z.; TAGHIZADEH-MEHRJARDI, R.; TAGUAS, E.; TEIXEIRA, W. G.; VAEZI, A. R.; VAFAKHAH, M.; VOGEL, T.; VOGELER, I.; VOTRUBOVA, J.; WERNER, S.; WINARSKI, T.; YILMAZ, D.; YOUNG, M. H.; ZACHARIAS, S.; ZENG, Y.; ZHAO, Y.; ZHAO, H.; VEREECKEN, H. Development and analysis of the Soil Water Infiltration Global database. Earth System Science Data, v. 10, n. 3, p. 1237-1263, 2018.Biblioteca(s): Embrapa Solos. |
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