High-throughput computational methods and software for quantitative trait locus (QTL) mapping

Danny Arends

High-throughput computational methods and software for quantitative trait locus (QTL) mapping

Vertaalde titel van de bijdrage: High-throughput computationele methoden en software voor quantitative trait locus (QTL) mapping

Danny Arends

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De afgelopen jaren zijn vele nieuwe technologieen zoals Tiling arrays en High throughput
DNA sequencing een belangrijke rol gaan spelen binnen het onderzoeksveld van de systeem genetica.
Voor onderzoekers is het extreem belangrijk om te begrijpen dat deze methodes hun manier van
werken zullen gaan beinvloeden. Deit proefschrift beschrijft mogelijke oplossingen voor deze 'Big Data'
lawine die systemen genetica heeft getroffen.

Dit proefschrift beschrijft de werkzaamheden uitgevoerd aan het Groningen Bioinformatics Centre om
slimmere en geoptimaliseerde algoritmen zoals Pheno2Geno en MQM te ontwikkelen en een systeem om
'collaborative' research mogelijk te maken genaamd xQTL werkbank om door middel van high-throughput
systemen genetica data te analyseren.

Vertaalde titel van de bijdrage	High-throughput computationele methoden en software voor quantitative trait locus (QTL) mapping
Originele taal-2	English
Kwalificatie	Doctor of Philosophy
Toekennende instantie	Rijksuniversiteit Groningen
Begeleider(s)/adviseur	Jansen, Ritsert, Supervisor Swertz, Morris, Co-supervisor
Datum van toekenning	17-okt.-2014
Gedrukte ISBN's	978-90-367-7210-5
Elektronische ISBN's	978-90-367-7209-9
Status	Published - 2014

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title = "High-throughput computational methods and software for quantitative trait locus (QTL) mapping",

abstract = "In recent years many new technologies such as tiling arrays and high-throughput sequencinghave come to play an important role in systems genetics research. For researchers it is ofthe utmost importance to understand how this affects their research. This work describespossible solutions to this {\textquoteleft}Big Data{\textquoteright} avalanche which has hit systems genetics.This thesis describes the work carried out during the author{\textquoteright}s 4 year PHD project at theGroningen Bioinformatics Centre to develop smarter and more optimized algorithms suchas Pheno2Geno and MQM, and to use a collaborative approach such as xQTL workbench tostore and analyse high-throughput systems genetics data.",

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year = "2014",

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TY - BOOK

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AU - Arends, Danny

PY - 2014

Y1 - 2014

N2 - In recent years many new technologies such as tiling arrays and high-throughput sequencinghave come to play an important role in systems genetics research. For researchers it is ofthe utmost importance to understand how this affects their research. This work describespossible solutions to this ‘Big Data’ avalanche which has hit systems genetics.This thesis describes the work carried out during the author’s 4 year PHD project at theGroningen Bioinformatics Centre to develop smarter and more optimized algorithms suchas Pheno2Geno and MQM, and to use a collaborative approach such as xQTL workbench tostore and analyse high-throughput systems genetics data.

AB - In recent years many new technologies such as tiling arrays and high-throughput sequencinghave come to play an important role in systems genetics research. For researchers it is ofthe utmost importance to understand how this affects their research. This work describespossible solutions to this ‘Big Data’ avalanche which has hit systems genetics.This thesis describes the work carried out during the author’s 4 year PHD project at theGroningen Bioinformatics Centre to develop smarter and more optimized algorithms suchas Pheno2Geno and MQM, and to use a collaborative approach such as xQTL workbench tostore and analyse high-throughput systems genetics data.

M3 - Thesis fully internal (DIV)

SN - 978-90-367-7210-5

ER -

High-throughput computational methods and software for quantitative trait locus (QTL) mapping

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