LIPIcs, Volume 258, SoCG 2023, Complete Volume

LIPIcs, Volume 258, SoCG 2023, Complete Volum

On the topology Of network fine structures

Multi-relational dynamics are ubiquitous in many complex systems like transportations, social and biological. This thesis studies the two mathematical objects that encapsulate these relationships --- multiplexes and interval graphs. The former is the modern outlook in Network Science to generalize the edges in graphs while the latter was popularized during the 1960s in Graph Theory. Although multiplexes and interval graphs are nearly 50 years apart, their motivations are similar and it is worthwhile to investigate their structural connections and properties. This thesis look into these mathematical objects and presents their connections. For example we will look at the community structures in multiplexes and learn how unstable the detection algorithms are. This can lead researchers to the wrong conclusions. Thus it is important to get formalism precise and this thesis shows that the complexity of interval graphs is an indicator to the precision. However this measure of complexity is a computational hard problem in Graph Theory and in turn we use a heuristic strategy from Network Science to tackle the problem. One of the main contributions of this thesis is the compilation of the disparate literature on these mathematical objects. The novelty of this contribution is in using the statistical tools from population biology to deduce the completeness of this thesis's bibliography. It can also be used as a framework for researchers to quantify the comprehensiveness of their preliminary investigations. From the large body of multiplex research, the thesis focuses on the statistical properties of the projection of multiplexes (the reduction of multi-relational system to a single relationship network). It is important as projection is always used as the baseline for many relevant algorithms and its topology is insightful to understand the dynamics of the system.Open Acces

Enumerative Combinatorics

Enumerative Combinatorics focusses on the exact and asymptotic counting of combinatorial objects. It is strongly connected to the probabilistic analysis of large combinatorial structures and has fruitful connections to several disciplines, including statistical physics, algebraic combinatorics, graph theory and computer science. This workshop brought together experts from all these various fields, including also computer algebra, with the goal of promoting cooperation and interaction among researchers with largely varying backgrounds

Investigating pathogen-host interactions and adaptation with network biology approaches

Serovars of the genus Salmonella are widespread enteric pathogens, causing acute inflammatory gut infections. However, a subgroup of Salmonella adapted to a systemic lifestyle instead of a mucosal one. A systems-level understanding of how molecular level changes accompanying this adaptive process potentially modify the behaviour of these invasive strains is crucial for future intervention processes, and possible treatments. In this thesis, I generated and analysed multi-layered interaction networks for 20 strains in the genus Salmonella. I collated protein-protein, transcriptional regulatory, and metabolic interaction data from low and high-throughput experiments and performed predictive measures to add further connections to the systems. The resulting networks culminated in the update to SalmoNet, the first integrated network database for Salmonella serovars. Through comparative network approaches, users can highlight elements under selection in these invasive serovars, increasing our understanding of the host adaptation process leading to their systemic lifestyle. During the last year of my PhD, I redeployed for 6 months to work on COVID-19 related research. This effort led to a systematic literature curation highlighting different cytokine responses in patients caused by SARS-CoV-2 compared to other similar viruses. I also led the effort to establish a new network resource, CytokineLink, aimed at highlighting avenues of cell-to-cell communication mediated by cytokines, to better understand inflammatory and infectious diseases. Overall, the work presented in this thesis has increased our understanding of the Salmonella host adaptation process, by highlighting specific elements under selection, while also exhibiting how network information can be created, and used for understanding such evolutionary processes