## From BIMIBRevision as of 11:54, 14 November 2016 by Marco.antoniotti (talk | contribs) ## ResearchThe research activities of the Bioinformatics Laboratories of the DISCo are centered around a number of projects, loosely grouped around the themes of
## Contents## Systems Biology and Data Analysis## Cancer ResearchOne of the most interesting problems in Cancer Research concerns the
## RetroNetThe analysis of biological systems relies more and more on computational and mathematical methods. The goals of such analysis are multifarious; among the most important ones is the discovery of the biochemical and genetic machinery responsible for pathology development, its control and, possibly, elimination. Such discoveries also rely on an understanding of the spatio-temporal development of biological phenomena, their cause (often "mutations") and their effects on different scales. The RetroNet project intends to address this problem and others by i) sharing data and knowledge needed for a new integrative research approach in medicine, ii) sharing or jointly develop multiscale models, simulators and analysis tools, with particular attention to the development of Colon Rectal Cancer (CRC) and some of its metastatic effects, and, iii) creating the prototype of a collaborative environment supporting research in this highly interdisciplinary field, by leveraging the experience matured from of previous FP6 experiences . The RetroNet project concentrates on the development and tuning of algorithms for detecting of emerging behavior from cells ensembles, by searching, analysing and formulating hypotheses of various feedback cycles in biological systems. The approach will leverage several
## NEUROWEBThe amount of biomedical information that can be accessed through the Internet has reached a level no one could have dreamt of just ten years ago. The success of the genome sequencing projects has created an enormous amount of data that cannot be manually analysed. Since disease phenotypes arise from complex interaction between genetic factors and environment, the value of high-throughput genomic research would be dramatically enhanced by associations with key patient data. These data are generally available but of disparate quality and sources.The development of a data management system which integrates genomic databanks, clinical databases, and data mining tools embedded into a common resource accessible to health care professionals would be extremely advantageous. Ischemic stroke is a major health problem in the developed countries. It is a complex, multigenic disorder, since there are several subtypes and risk factors, and most of the cases have non-mendelian inheritance. The integration and the analysis of a large number of well-defined clinical, radiological and molecular data will improve the evidence on the different roles played by genetic and environmental risk factors in stroke pathophysiology. NEUROWEB was funded by the European Commission in the FP6 program. The project identifier was IST-2006-518513.
## BRONTEThe
## Bioinformatics and Sequence Analysis## ASPIc
## Phylogenetic Reconstruction and ComparisonOur research on this basic topic of Computational Biology mainly concerns the computational complexity and algorithmic solution of optimization problems derived by specific instances of the more general problem of comparing phylogenies (or evolutionary networks) to combine them into a single representation (i.e. an evolutionary tree or network). We address computational problems derived from consensus tree methods such as the ## Algorithms for Haplotype Inference (HI) and Genetic Variation AnalysisOur research in this field is mainly focused on the design and experimentation of algorithm for solving combinatorial problems related to haplotype inference and genetic variations analysis. Specific computational problems of interest are: (1) inferring the complete information on haplotypes from (incomplete or partial) haplotypes or genotypes assuming the Coalescent model, (2) efficient reconstruction of the perfect phylogeny describing the evolutionary history of SNPs (single nucleotide polymorphism) data in presence of recurrent mutations. ## Sequence Analysis and ComparisonThe main goal of this project concerns the development of algorithms for sequence analysis by novel alignment methodology and sequence comparison by consensus sequence methods with application in several field of genome sequence comparison (genome sequence rearrangement, multiple sequence comparison). Our investigation in this area has concerned the design of approximation and heuristic algorithms for the LCS and SCS, the Exemplar Longest Common Subsequence.
## Natural Computing## Splicing systems and regular languagesIn our research, we focus on the original concept of finite splicing system that is closest to the real biological process: the splicing operation is meant to act by a finite set of rules (modeling enzymes) on a finite set of initial strings (modeling DNA sequences). Under this formal model, a
## Experimental AlgorithmicsThe main activity carried on in this lab is to design efficient algorithms for solving a number of combinatorial problems. Both theoretical and practical aspects are studied, as efficiency is sought at the algorithmic and implementation levels. Consequently it is of fundamental relevance the design and implementation of efficient data structures. Ongoing research is focused on the design of approximation and exact algorithm, as well as the analysis of algorithms. The analysis can be on the average case and on the worst case. The techniques employed can be mathematical and combinatorial when the emphasis is on the theoretical side, while an experimental study is preferred when the real-world behavior is analyzed. More information can be found on the main page of the ALGO-lab. |