New sequencing strategies have redefined the concept of “high-throughput sequencing” and many companies, researchers, and recent reviews use the term “Next-Generation Sequencing” (NGS) instead of high-throughput sequencing. These advances have introduced a new era in genomics and bioinformatics⁠⁠. During my years as PhD student I have developed various software, algorithms and procedures for the analysis of Nest Generation sequencing data required for distinct biological research projects and collaborations in which our research group was involved. The tools and algorithms are thus presented in their appropriate biological contexts. Initially I dedicated myself to the development of scripts and pipelines which were used to assemble and annotate the mitochondrial genome of the model plant Vitis vinifera. The sequence was subsequently used as a reference to study the RNA editing of mitochondrial transcripts, using data produced by the Illumina and SOLiD platforms. I subsequently developed a new approach and a new software package for the detection of of relatively small indels between a donor and a reference genome, using NGS paired-end (PE) data and machine learning algorithms. I was able to show that, suitable Paired End data, contrary to previous assertions, can be used to detect, with high confidence, very small indels in low complexity genomic contexts. Finally I participated in a project aimed at the reconstruction of the genomic sequences of 2 distinct strains of the biotechnologically relevant fungus Fusarium. In this context I performed the sequence assembly to obtain the initial contigs and devised and implemented a new scaffolding algorithm which has proved to be particularly efficient.

BIOINFORMATIC TOOLS FOR NEXT GENERATION GENOMICS / M. Chiara ; tutor: D. S Horner. - : . Universita' degli Studi di Milano, 2012 Apr 20. ((24. ciclo, Anno Accademico 2011. [10.13130/chiara-matteo_phd2012-04-20].

BIOINFORMATIC TOOLS FOR NEXT GENERATION GENOMICS

M. Chiara
2012-04-20

Abstract

New sequencing strategies have redefined the concept of “high-throughput sequencing” and many companies, researchers, and recent reviews use the term “Next-Generation Sequencing” (NGS) instead of high-throughput sequencing. These advances have introduced a new era in genomics and bioinformatics⁠⁠. During my years as PhD student I have developed various software, algorithms and procedures for the analysis of Nest Generation sequencing data required for distinct biological research projects and collaborations in which our research group was involved. The tools and algorithms are thus presented in their appropriate biological contexts. Initially I dedicated myself to the development of scripts and pipelines which were used to assemble and annotate the mitochondrial genome of the model plant Vitis vinifera. The sequence was subsequently used as a reference to study the RNA editing of mitochondrial transcripts, using data produced by the Illumina and SOLiD platforms. I subsequently developed a new approach and a new software package for the detection of of relatively small indels between a donor and a reference genome, using NGS paired-end (PE) data and machine learning algorithms. I was able to show that, suitable Paired End data, contrary to previous assertions, can be used to detect, with high confidence, very small indels in low complexity genomic contexts. Finally I participated in a project aimed at the reconstruction of the genomic sequences of 2 distinct strains of the biotechnologically relevant fungus Fusarium. In this context I performed the sequence assembly to obtain the initial contigs and devised and implemented a new scaffolding algorithm which has proved to be particularly efficient.
HORNER, DAVID STEPHEN
bioinformatics ; comparative genomics ; genome assembly ; scaffolding ; structural variations;
Settore BIO/11 - Biologia Molecolare
BIOINFORMATIC TOOLS FOR NEXT GENERATION GENOMICS / M. Chiara ; tutor: D. S Horner. - : . Universita' degli Studi di Milano, 2012 Apr 20. ((24. ciclo, Anno Accademico 2011. [10.13130/chiara-matteo_phd2012-04-20].
Doctoral Thesis
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2434/173424
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