
Tor Marketplaces Exploratory Data Analysis: The Drugs Case
The anonymous marketplaces ecosystem represents a new channel for black market/goods and services, offering a huge variety of illegal items.
Analysing the Tor Web with High Performance Graph Algorithms
The exploration and analysis of Web graphs has flourished in the recent past, producing a large number of relevant and interesting research results. However, the unique characteristics of the Tor network demand for specific algorithms to explore and analyze it. Tor is an anonymity network that allows offering and accessing various Internet resources while guaranteeing a high degree of provider and user anonymity. So far the attention of the research community has focused on assessing the security of the Tor infrastructure.
Modeling the Effect of High Calorie Diet on the Interplay between Adipose Tissue, Inflammation, and Diabetes
Background. Type 2 diabetes (T2D) is a chronic metabolic disease potentially leading to serious widespread tissue damage. Human organism develops T2D when the glucose-insulin control is broken for reasons that are not fully understood but have been demonstrated to be linked to the emergence of a chronic inflammation. Indeed such low-level chronic inflammation affects the pancreatic production of insulin and triggers the development of insulin resistance, eventually leading to an impaired control of the blood glucose concentration.
Optimizing emergency transportation through multicommodity quickest paths
In transportation networks with limited capacities and travel times on the arcs, a class of problems attracting a growing scientific interest is represented by the optimal routing and scheduling of given amounts of flow to be transshipped from the origin points to the specific destinations in minimum time. Such problems are of particular concern to emergency transportation where evacuation plans seek to minimize the time evacuees need to clear the affected area and reach the safe zones.
A Machine Learning Approach for Disease Genes Signatures
In the context of network medicine, disease genes, i.e. genes that have been experimentally associated to the onset or progression of a pathology, show a complex set of features that are not easily reduced to, and grasped by a simple network approach (e.g., studying centrality measures or clustering characteristics of the gene network).
Potential predictors of type-2 diabetes risk: machine learning, synthetic data and wearable health devices
Investigation about the mechanisms involved in the onset of type 2 diabetes in absence of familiarity is the focus of a research project which has led to the development of a computational model that recapitulates the aetiology of the disease.
A Data Extraction and Visualization Framework for Information Retrieval Systems
In recent years we are witnessing a continuous growth in the amount of data that both public and private organizations collect and profit by. Search engines are the most common tools used to retrieve information, and more recently, clustering techniques showed to be an effective tool in helping users to skim query results.
Computational Immunology and Network Medicine
Presentazione delle attività di ricerca su computational immunology e network medicine al workshop "Hot Topics in Systems" all'interno della conferenza PLACE2019





