Pandemics of plague have reemerged multiple times throughout human history with tremendous mortality and extensive geographic spread. The First Pandemic (6th - 8th century) devastated the Mediterranean world, the Second Pandemic (14th - 19th century) swept across much of Afro-Eurasia, and the Third Pandemic (19th - 20th century) reached every continent except for Antarctica, and continues to persist in various endemic foci around the world. Despite centuries of historical research, the epidemiology of these pandemics remains enigmatic. However, recent technological advancements have yielded a novel form of evidence: ancient DNA of the plague bacterium Yersinia pestis. In this thesis, I explore how genomic data can be used to unravel the mysteries of when and where this disease appeared in the past. In particular, I focus on phylogenetic approaches to studying this 'small microbe' with 'big data' (i.e. 100s - 1000s of genomes). I begin by describing novel software I developed that supports the acquisition and curation of large amounts of DNA sequences in public databases. I then use this tool to create an updated global phylogeny of Y. pestis, which includes ~600 genomes with standardized metadata. I devise and validate a new approach for temporal modeling (i.e. molecular clock) that produces robust divergence dates in pandemic lineages of Y. pestis. In addition, I critically examine the questions that genomic evidence can and cannot address in isolation, such as whether the timing and spread of short-term epidemics can be confidently reconstructed. Finally, I apply this theoretical and methodological insight to a case study in which I reconstruct the appearance, persistence, and disappearance of plague in Denmark during the Second Pandemic. The three papers enclosed in this sandwich-thesis contribute to a larger body of work on the anthropology of plague, which seeks to understand how disease exposure and experience change over time and between human populations. Furthermore, this dissertation more broadly impacts both prospective studies of infectious disease, such as environmental surveillance and outbreak monitoring, and retrospective studies, which seek to date the emergence and spread of past pandemics. / Dissertation / Doctor of Philosophy (PhD) / The Plague is a disease that has profoundly impacted human history and is responsible for some of the most fatal pandemics ever recorded. It may surprise many to know that this disease is not a bygone of a past era, but in fact is still present in many regions of the world. Although researchers have been studying plague for hundreds of years, there are many aspects of its epidemiology that are enigmatic. In this thesis, I focus on how DNA from the plague bacterium can be used to estimate where and when this disease appeared in the past. To do so, I reconstruct the evolutionary relationships between modern and ancient strains of plague, using publicly available data and new DNA sequences retrieved from the skeletal remains of plague victims in Denmark. This work offers a new methodological framework for large-scale genetic analysis, provides a critique on what questions DNA evidence can and cannot answer, and expands our knowledge of the global diversity of plague.

This diploma thesis deals with the description of homologous genes and molecular biological databases that are used for their search and allow comparison. Among the most important institutions that deal with data management and analysis, include the EBI, NCBI and CIB. For searching homologous genes is the most fundamental NCBI - National Center for Biotechnology Information. More attention is paid to the search algorithms of homologous genes such as BLASTN and PatternHunter. The practical part of this thesis is the implementation of the algorithm comparing two sequences and locating homologous genes. The comparison is made on the basis of the nucleotide sequence and amino acid sequence. The results generated from the program will be further compared with results from commercially available programs.