Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.

Can gut microbiota analysis be beneficial for ex-situ and in-situ conservation of threatened animal species?

Ex-situ conservation and the in-situ conservation of natural habitats are the tools to conserve biodiversity. Habitats and ecosystems have been becoming altered by human activities and a growing number of species requires form of management to ensure their survival. Conservation queries become more complex and urgent. Developing scientifically based and innovative approaches to ex-situ conservation is necessary. Recent studies underline importance of gut microbiome in animal health with implications for animal conservation and management. Animal and human studies have demonstrated that environmental factors can impact gut microbiome composition. Within this scenario, the present work focused on species belonging to different taxa, reptiles and mammals: Aldabrachelys gigantea, the giant tortoise of the Seychelles islands and Indri indri, the greatest leaving lemur of Madagascar. The Seychelles giant tortoise is vulnerable species with declining population, whereas the indri is a critically endangered species that could reach the extinction within 25 years. Both need research to help them to survive. Tortoises live for very long time and to observe how they can afford the environmental changes is very difficult. Indris, instead, are able to survive only in a small area of the Madagascar forest, with a very strong link between the species’ survival and the environment. The obtained results underline importance of environmental factors, both in-situ and ex-situ, for species conservation. Microbiome could help the organisms to respond on a short timescale and cope with, environmental changes. However, species with long generation time might not be able to adapt to fast changes but bacteria with a short generation time can adapt on a shorter timescale allowing the host to cope with fluctuating environment. Gut microbiome plays an important role in an animal’s health and has the potential to improve the management of individuals under human care for conservation purposes.

The Simon effect and its time courses: an investigation

The objective of the current thesis is to investigate the temporal dynamics (i.e., time courses) of the Simon effect, both from a theoretical and experimental point of view, for a better understanding of whether a) one or more process are responsible for the Simon effect and b) how this/these mechanism/s differently influence performance. In the first theoretical (i.e., “Theoretical Overview”) part, I examined in detail the process and justification for analyzing the temporal dynamics of the Simon effect and the assumptions that underlie interpretation of the results which have been obtained in the existing literature so far. In the second part (“Experimental Investigations”), though, I experimentally investigated several issues which the existing literature left unsolved, in order to get further evidence in favor or in contrast with the mainstream models which are currently used to account for the different Simon effect time courses. Some points about the experiments are worth mentioning: First, all the experiments were conducted in the laboratory, facing participants with stimuli presented on a PC screen and then recording their responses. Both stimuli presentation and response collection was controlled by the E-Prime software. The dependent variables of interest were always behavioral measures of performance, such as velocity and accuracy. Second, the most part of my experiments had been conducted at the Communication Sciences Department (University of Bologna), under Prof. Nicoletti’s supervision. The remaining part, though, had been conducted at the Psychological Sciences Department of Purdue University (West Lafayette, Indiana, USA), where I collaborated for one year as a visiting student with Prof. Proctor and his team. Third, my experimental pool was entirely composed by healthy and young students, since the cognitive functioning of elderly people was not the target of my research.