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Abstract
From the beginning of sequencing the comparison of sequences has played a center role in bioinformatics. Here computer-based methods have successfully been deployed to enable efficient alignment of sequences, which has evolved ever since to meet the requirements set by new technologies and scientific curiosity. Today sequencing is used to answer various questions, leading to an immense amount of sequencing data being produced every day. Over the last decade we have seen more and more surveillance and diagnostics institutions that have started to include sequencing as part of their analysis tool package for microbial analysis. This trend of microbial sequence analysis has led to a number of bioinformatic methods to detect genes, compare genomes and discover novelty within microbes. Common for these methods were that they were computationally heavy, and for efficient and timely analysis it required large cluster computers to keep up with the sequencing data that were produced. This requirement has limited the use of sequencing as a general tool by many institutions, and placed a requirement for more efficient bioinformatic methods, if the trend of sequencing is to advance. The aim of this PhD was to develop new improved algorithms, that allows typing and phenotyping of microbial sequence data based on direct analysis of the raw sequence data. Difficulties and challenges have been explored by the development of new methods, as well as exploring methods and algorithms in use
today.
today.
Original language | English |
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Place of Publication | Kgs. Lyngby |
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Publisher | Technical University of Denmark |
Number of pages | 70 |
Publication status | Published - 2020 |
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Dive into the research topics of 'Typing and phenotyping based on direct sequencing of samples'. Together they form a unique fingerprint.Projects
- 1 Finished
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Typing and pheno typing based on direct sequencing of samples
Clausen, P. T. L. C. (PhD Student), Phillippy, A. (Examiner), Kaas, R. S. (Examiner), Krogh, A. (Examiner), Lund, O. (Main Supervisor) & Aarestrup, F. M. (Supervisor)
01/07/2017 → 15/09/2020
Project: PhD