@phdthesis{Ankenbrand2018,
  author    = {Ankenbrand, Markus Johannes},
  title     = {Squeezing more information out of biological data - development and application of bioinformatic tools for ecology, evolution and genomics},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-156344},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {New experimental methods have drastically accelerated the pace and quantity at which biological data is generated. High-throughput DNA sequencing is one of the pivotal new technologies. It offers a number of novel applications in various fields of biology, including ecology, evolution, and genomics. However, together with those opportunities many new challenges arise. Specialized algorithms and software are required to cope with the amount of data, often requiring substantial training in bioinformatic methods. Another way to make those data accessible to non-bioinformaticians is the development of programs with intuitive user interfaces. In my thesis I developed analyses and programs to tackle current problems with high-throughput data in biology. In the field of ecology this covers the establishment of the bioinformatic workflow for pollen DNA meta-barcoding. Furthermore, I developed an application that facilitates the analysis of ecological communities in the context of their traits. Information from multiple public databases have been aggregated and can now be mapped automatically to existing community tables for interactive inspection. In evolution the new data are used to reconstruct phylogenetic trees from multiple genes. I developed the tool bcgTree to automate this process for bacteria. Many plant genomes have been sequenced in current years. Sequencing reads of those projects also contain data from the chloroplasts. The tool chloroExtractor supports the targeted extraction and analysis of the chloroplast genome. To compare the structure of multiple genomes specialized software is required for calculation and visualization of the relationships. I developed AliTV to address this. In contrast to existing programs for this task it allows interactive adjustments of produced graphics. Thus, facilitating the discovery of biologically relevant information. Another application I developed helps to analyze transcriptomes even if no reference genome is present. This is achieved by aggregating the different pieces of information, like functional annotation and expression level, for each transcript in a web platform. Scientists can then search, filter, subset, and visualize the transcriptome. Together the methods and tools expedite insights into biological systems that were not possible before.},
  language  = {en}
}
@phdthesis{Gupta2018,
  author    = {Gupta, Shishir Kumar},
  title     = {Re-annotation of Camponotus floridanus Genome and Characterization of Innate Immunity Transcriptome Responses to Bacterial Infections},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-140168},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {The sequencing of several ant genomes within the last six years open new research avenues for understanding not only the genetic basis of social species but also the complex systems such as immune responses in general. Similar to other social insects, ants live in cooperative colonies, often in high densities and with genetically identical or closely related individuals. The contact behaviours and crowd living conditions allow the disease to spread rapidly through colonies. Nevertheless, ants can efficiently combat infections by using diverse and effective immune mechanisms. However, the components of the immune system of carpenter ant Camponotus floridanus and also the factors in bacteria that facilitate infection are not well understood. To form a better view of the immune repository and study the C. floridanus immune responses against the bacteria, experimental data from Illumina sequencing and mass-spectrometry (MS) data of haemolymph in normal and infectious conditions were analysed and integrated with the several bioinformatics approaches. Briefly, the tasks were accomplished in three levels. First, the C. floridanus genome was re-annotated for the improvement of the existing annotation using the computational methods and transcriptomics data. Using the homology based methods, the extensive survey of literature, and mRNA expression profiles, the immune repository of C. floridanus were established. Second, large-scale protein-protein interactions (PPIs) and signalling network of C. floridanus were reconstructed and analysed and further the infection induced functional modules in the networks were detected by mapping of the expression data over the networks. In addition, the interactions of the immune components with the bacteria were identified by reconstructing inter-species PPIs networks and the interactions were validated by literature. Third, the stage-specific MS data of larvae and worker ants were analysed and the differences in the immune response were reported. Concisely, all the three omics levels resulted to multiple findings, for instance, re-annotation and transcriptome profiling resulted in the overall improvement of structural and functional annotation and detection of alternative splicing events, network analysis revealed the differentially expressed topologically important proteins and the active functional modules, MS data analysis revealed the stage specific differences in C. floridanus immune responses against bacterial pathogens. Taken together, starting from re-annotation of C. floridanus genome, this thesis provides a transcriptome and proteome level characterization of ant C. floridanus, particularly focusing on the immune system responses to pathogenic bacteria from a biological and a bioinformatics point of view. This work can serve as a model for the integration of omics data focusing on the immuno-transcriptome of insects.},
  subject      = {Camponotus floridanus},
  language  = {en}
}