Bioinformatics and medical informatics

This area aims to develop and experiment computational models, computational platforms and algorithms arising in different contexts of applications originating from bioinformatics, biomedical informatics, robotics and multimedia systems. Concerning bioinformatics and biomedical applications, research focuses on several topics, as computational systems biology, natural computing, computational genomics, algorithmic bioinformatics, healthcare and clinical process-aware information systems, clinical databases and data warehouses, clinical data mining. Applied research in robotics deals mainly with applications for service robotics and field robotics, including all robotic systems that are not concerned with manufacturing operations: robotic surgery, exploration, elderly and disabled care, logistics and countermeasures against disaster and terrorism. Multimedia applications are related to biomedical data analysis and videosurveillance, investigating advanced techniques of image and signal processing, computer graphics and visualization, computer vision, machine learning and statistical pattern recognition.

Documents

pdf Brochure di presentazione dell'area  (pdf,  it, 246 KB)
pdf Presentazione Research Day 2017  (pdf,  it, 5733 KB)
Manuele Bicego
Associate Professor
Vincenzo Bonnici
Research Scholarship Holders
Umberto Castellani
Associate Professor
Alberto Castellini
Research Scholarship Holders
Ferdinando Cicalese
Associate Professor
Carlo Combi
Full Professor
Alessandro Daducci
Temporary Assistant Professor
Giuditta Franco
Assistant Professor
Rosalba Giugno
Associate Professor
Zsuzsanna Liptak
Assistant Professor
Vincenzo Manca
Full Professor
Luca Marchetti
Temporary Professor
Gloria Menegaz
Full Professor
Barbara Oliboni
Assistant Professor
Romeo Rizzi
Associate Professor
Skills
Topic People Description ISI-CRUI
Applied computing - Life and medical sciences standard compliant  ACM 2012
Algorithms for Bioinformatics Ferdinando Cicalese
Our research focuses on design of algorithms for the management and analysis of large scale biological data (e.g. -omics data of different types). Our research is driven by the idea that modern data sciences can contribute significantly to address important questions in life sciences. Algorithms from the fields of search theory (group testing), active learning, and data mining (particularly in sequences and networks), as well as, information theoretic approaches based on entropic analysis, can be used to support the causal understanding, diagnosis and prognosis of complex diseases. Computer Science & Engineering
Algorithmic bioinformatics Zsuzsanna Liptak
We develop algorithms for discrete problems arising from computational biology, among these: algorithms for mass spectrometry data interpretation, clustering of transcriptomic data, non-alignment based sequence comparison. Computer Science & Engineering
Bioinformatics and Computational Biology Manuele Bicego
Design and testing of Pattern Recognition and Machine Learning techniques for the analysis and understanding of biological data. In particular the main focus in on designing solutions for the analysis of "counting data" - namely data which express the level of presence of entities (e.g. gene expression data, or proteomics data) - using probabilistic graphical models like topic models. The main goal is to devise highly interpretable solutions, being interpretability of methods and solutions the most stringent need in nowadays bioinformatics research.
Bioinformatics and Natural Computing Vincenzo Bonnici
Alberto Castellini
Giuditta Franco
Rosalba Giugno
Vincenzo Manca
Luca Marchetti
Roberto Pagliarini
Our research is mainly focused on the following topics: 1) Discrete and algorithmic analyses of biological dynamics (metabolism and replication, and their interplay in cellular processes); 2) Informational and computational analysis of genomes (genomic dictionaries, genomic indexes, genomic distributions of specific parameters, genome representations, genome synthesis and reconstruction from dictionaries). In these research areas, theories and algorithms are investigated and software packages are developed for computational experiments and analyses. Computer Science & Engineering
Biological network dynamics Giuditta Franco
Design and analysis of data-driven computational models, for both metabolic and immunological dynamics, based on grammars ruled by state functions. Biological network dynamical properties are investigated in terms of discrete mathematics and model simulation. Membrane and metabolic computing for biological modeling. Genetic network investigation based on computational genomics studies. Computer Science & Engineering
Computational genomics and DNA computing Giuditta Franco
Investigation and classification of genomic sequences by means of information theory based methods. Design and analysis of both bio-inspired and molecular algorithms, along with their lab implementation. Computer Science & Engineering
Neuroimaging Umberto Castellani
Alessandro Daducci
Gloria Menegaz
The main activity is in the field of neuroimaging, including structural (diffusion MRI) and functional (EEG, fNIRS, functional MRI) imaging as well as perceptual analysis through cognitive science methods. The goal is to gain an holistic view of human brain when inspected in specific conditions by the integration of multi-modal multi-scale probing and modeling. In addition, advanced computer vision and pattern recognition methods are employed for designing numerical biomarkers for the characterization of healthy and pathological conditions. Computer Science & Engineering
Health Information Systems Carlo Combi
Barbara Oliboni
Main research interests to the management of clinical information in medical records and to the management of clinical processes/guidelines. More precisely main topics are: - temporal information systems in medicine; - temporal workflow systems in medicine and healthcare: modeling issues and architectures; - temporal and multimedia clinical databases; - temporal data warehouses and temporal data mining for health/clinical knowledge discovery; - visualizing temporal and multimedia clinical data; - Web-based access to clinical information. Computer Science & Engineering
Systems Biology, Computational Network Biology Rosalba Giugno
Design of algorithms and methods to understand biological systems using data mining and bioinformatics techniques. The focus is on biological network modeling, perturbation and analysis; classification of phenotypes by coding and non-coding expression profiles; drug synergy and mechanism of action by drug target/off-target/combination prediction. Computer Science & Engineering
Applied computing - Operations research standard compliant  ACM 2012
Operations research Romeo Rizzi
Operations research is a discipline that deals with the application of advanced analytical methods to help make better decisions. The terms management science and decision science are sometimes used as more modern-sounding synonyms. Employing techniques from other mathematical sciences, such as mathematical modeling, statistical analysis, and mathematical optimization, operations research arrives at optimal or near-optimal solutions to complex decision-making problems. Operations Research is often concerned with determining the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost) of some real-world objective. Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries. Besides its applications in industry and in management, Operations Research is at the very junction of mathematics and economics. Operations research embodies lots of deep results and theory but, at the same time, it is the archetype of applied mathematics. In Verona, we draw applications of the tools and methodologies of operations research to computational biology. More generally, we actively work in combinatorial optimization and contribute to algorithmic graph theory. We also apply and express methods and competencies of mathematical programming. In mathematics, statistics, empirical sciences, computer science, or management science, mathematical optimization (alternatively, mathematical programming) is the selection of a best element (with regard to some criteria) from some set of available alternatives. Here, optimization includes finding "best available" values of some objective function given a defined domain, including a variety of different types of objective functions and different types of domains. Optimization theory, techniques, and algorithms, comprises a large area of applied mathematics. Among the many sectors of mathematical programming, some of those represented in Verona are the following: linear programming, integer linear programming, combinatorial optimization, multiobjective optimization. Computer Science & Engineering
Gruppi di ricerca
Name Description URL
Basi di dati e Sistemi Informativi Questo gruppo di ricercatori si occupa di varie tematiche nell'ambito dei sistemi informativi http://stars.di.univr.it
Bioinformatica e Calcolo Naturale Analisi algoritmica di processi biologici http://bioinformatics.di.univr.it/
Visione ed elaborazione delle immagini e suoni (VIPS - Vision, Image Processing & Sound) Computer Vision and Pattern Recognition, Image Processing, and Sound Analysis & Processing http://vips.sci.univr.it/
Projects
Title Managers Sponsors Starting date Duration (months)
AHeAD - Automatic Human behavior Analysis in neurological Diseases: the case of epilepsy - Joint Projects 2012 Gloria Menegaz Ateneo, EB Neuro SpA 9/18/13 24
Brain microstructural modeling for improved TMS anchoring - Joint Projects 2015 Gloria Menegaz EB Neuro SpA 7/1/16 24
DNA Computing e modelli di interazione intracellulare Vincenzo Manca Ministero dell'Istruzione dell'Università e della Ricerca 5/10/02 24
Fusione e quality assesment di immagini da TC volumetrica "cone beam" Gloria Menegaz QR s.r.l. 7/1/13 12
Investigation of structural and functional brain connectivity from multimodal data - Joint Projects 2014 Gloria Menegaz Ateneo, EB Neuro SpA 1/1/15 24

Activities

Research facilities