The overarching aim of the NANOSOLUTIONS consortium is to provide a means to develop a safety classification for engineered nanomaterials (ENM) based on an understanding of their interactions with living organisms at molecular, cellular and organism levels.
The objective is to determine the “biological identity” of ENM, and subsequently develop a computer program that can predict from the properties of ENM their ability to cause health or environmental hazards. New innovative methods are needed for the ENM risk assessment of ENM safety, i.e. ENM SAFETY CLASSIFIER.
This will allow for the crucial transition from descriptive toxicology to predictive toxicology.
The IEEE Italy Section CIS Chapter, in the next years, will aim to increase the diffusion of Computational Intelligence methods in Italy. The principal considered scenarios, but not the only ones, are industrial and biomedical applications, since in the ICT context, neural-based techniques, fuzzy methods, and evolutionary algorithms can be considered as the ones offering the greatest additional value in the realization of innovative systems and products, which are enabling factors for the recovery and grow of the Italian economy. The Chapter therefore aims to stimulate new initiatives supporting the communication between Italian researchers working in Computational Intelligence, and the training of young people in this field. One of the instruments that will be used is the new web platform, which will permit to share information on national and local events, and will facilitate iterations between the Italian members of the Chapter.
NeaPolis Innovation Campus 2014 è un’iniziativa pensata per facilitare le scelte professionali degli studenti dei corsi di laurea delle materie tecnico-scientifiche attraverso la conoscenza diretta del mondo del lavoro. Un’esperienza nelle sedi di STMicroelectronics in Campania è un’opportunità per sperimentare il lavoro di squadra, immersi in un’azienda che è leader mondiale nello sviluppo e nell’offerta di soluzioni basate sui semiconduttori per ogni tipo di applicazione microelettronica.
Leaf is a Python tool for the design and management of Bioinformatic Protocols, also known as data flows. We call them “protocols” to stress the importance of producing data flows that make design, execution, maintenance, sharing and reproduction of data analysis processes as efficient as possible. Leaf was developed in a Bioinformatic environment, but can be used in any data analysis project. Leaf is mainly implemented in Python, which can be easily interfaced with other languages such as R.
MIDA is a Cluster Analysis tool for the Matlab environment aimed to simplify and improve the analysis of hierarchically organized data. A dendrogram is a visualization of a hierarchy relationship between a set of items, based on a tree with length of the edges corresponding to distances between groups of items. By cutting the tree, a forest is obtained corresponding to a clustering. Dendrograms are used in a huge quantity of different applications and research areas. At the core of MIDA there’s an interactive dendrogram, offering functionalities such as visually selecting subtrees and setting the cut treshold. A screenshot of the MIDA core follows.