The Biocomputing group of the University of Bologna became officially active in 1995. Since then research interests focus on different aspects of genomics, proteomics and more recently Systems Biology. The main focus of the group is the designing and implementation of algorithms based on methods out of machine learning/statistical/probabilistic approaches for problem solving in computational biology and bioinformatics. Information retrieval is generally based on customised and selected data bases of genomics, proteomics, interactomics and metabolomics. The expertises of the Biocomputing Group include the following areas: Prediction of: Protein Secondary Structure Contact Maps Protein Folding Bonding State of Cysteines and Topology of Disulfide Bridges Protein Stability upon Mutation Phenotipic Effects of Protein Mutations Protein Biosequence Analysis and Annotation Protein Modelling, Molecular Docking and Molecular dynamics Fold recognisition Prediction of protein function from sequence and/or structure Protein-protein interaction and scaling to interactomics data bases Large scale genome/proteome annotation Alternative splicing annotation SNPs search and annotation The demand for such expertises is increasing due to the necessity of analysing and interpreting the flood of data made available by the adoption in the Next Generation Sequencing techniques, in both experimental and clinical contexts. The rational use of bio-computational techniques is essential for annotating the function and the structure of newly discovered sequences and for understanding the effects of the sequence variability between different individuals and cross species. The synergy between the new experimental techniques and the advanced tools for computational analysis promises to boost the knowledge on the biological mechanisms at the basis of different pathologies, including cancer and the most common genetic diseases, and it is then expected to lead to new diagnostic and prognostic tests and to innovative therapeutical practices.

Computational Biology and Bioinformatics

CASADIO, RITA
2010

Abstract

The Biocomputing group of the University of Bologna became officially active in 1995. Since then research interests focus on different aspects of genomics, proteomics and more recently Systems Biology. The main focus of the group is the designing and implementation of algorithms based on methods out of machine learning/statistical/probabilistic approaches for problem solving in computational biology and bioinformatics. Information retrieval is generally based on customised and selected data bases of genomics, proteomics, interactomics and metabolomics. The expertises of the Biocomputing Group include the following areas: Prediction of: Protein Secondary Structure Contact Maps Protein Folding Bonding State of Cysteines and Topology of Disulfide Bridges Protein Stability upon Mutation Phenotipic Effects of Protein Mutations Protein Biosequence Analysis and Annotation Protein Modelling, Molecular Docking and Molecular dynamics Fold recognisition Prediction of protein function from sequence and/or structure Protein-protein interaction and scaling to interactomics data bases Large scale genome/proteome annotation Alternative splicing annotation SNPs search and annotation The demand for such expertises is increasing due to the necessity of analysing and interpreting the flood of data made available by the adoption in the Next Generation Sequencing techniques, in both experimental and clinical contexts. The rational use of bio-computational techniques is essential for annotating the function and the structure of newly discovered sequences and for understanding the effects of the sequence variability between different individuals and cross species. The synergy between the new experimental techniques and the advanced tools for computational analysis promises to boost the knowledge on the biological mechanisms at the basis of different pathologies, including cancer and the most common genetic diseases, and it is then expected to lead to new diagnostic and prognostic tests and to innovative therapeutical practices.
CASADIO R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/101422
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