Unit QUANTITATIVE BIOLOGY

Course
Biology
Study-unit Code
55191206
Curriculum
Biomolecolare
Teacher
Francesco Morena
Teachers
  • Francesco Morena
Hours
  • 42 ore - Francesco Morena
CFU
6
Course Regulation
Coorte 2020
Offered
2020/21
Learning activities
Affine/integrativa
Area
Attività formative affini o integrative
Academic discipline
BIO/11
Type of study-unit
Opzionale (Optional)
Type of learning activities
Attività formativa monodisciplinare
Language of instruction
Italian
Contents
Introduction to bioinformatics. Use of the Internet and databases in Molecular Biology. Statistical techniques and algorithms. Applications of bioinformatics to biotechnology. Biological macromolecules. Genomic sequence analysis. Analysis of amino acid sequences. Structural biology. Computational and visualization techniques for structural bioinformatics. Molecular Docking.
Reference texts
Manuela Helmer Citterich, Fabrizio Ferrè, Giulio Pavesi, Graziano Pesole, Chiara Romualdi. Fondamenti di bioinformatica. Zanichelli

Pascarella, Paiardini. Bioinformatica: dalla sequenza alla struttura delle proteine. Zanichelli

Teaching material provided by the professor
Educational objectives
Provide students with the basic knowledge of Bioinformatics and its applications on the study of biological macromolecules: DNA, RNA and proteins, from sequence to structure; make them capable of linking the structure of these macromolecules to their function; provide them with the basic knowledge on the experimental tools that underlie the knowledge of molecular biology and biotechnology.
Prerequisites
In order to understand the topics covered in the course, the student must have the basic knowledge of Organic Chemistry, Biology, Biochemistry as regards the concepts of biological macromolecules, interactions between macromolecules, structure and function of proteins, enzymes.
Teaching methods
Frontal lectures in the classroom with slide shows and videos. Each lesson includes a practical / application part and for this reason they will be held in the bioinformatics classroom.
Other information
Supplementary teaching activities:
Tutoring is foreseen during the course and subsequently for students who request it to help them prepare for the exam.
Learning verification modality
They consist of a written test, followed by an oral one. The written test will serve to ascertain the level of knowledge and understanding of the topics covered during the course and will have a maximum duration of two hours, during which the student will have to answer thirty multiple choice questions and questions that require a short open answer. . An oral test will follow, to which students who have passed the written test with a mark equal to or greater than 18/30 will have access. This test will be used to clarify critical issues that emerged from the written test and to verify the student's communication skills with language properties and independent organization of the exhibition on the topics covered by the written test or in any case treated in class. The result of the written and oral test will compete for the final mark.
Students who have not passed the written test will have the opportunity to analyze the critical issues together with the teacher on the day of the oral test.

For information on support services for students with disabilities and / or DSA visit the page http://www.unipg.it/disabilita-e-dsa
Extended program
Bioinformatics: general characteristics. Data and Database: archiving and main query systems. Programming principles: Unix and Python. Statistical techniques and algorithms: Basic concepts on the calculation of probabilities`. Typical probability distributions` and statistical tests t-test and ANOVA. Markov Model and Hidden Markov Model.

Applications of bioinformatics to molecular and industrial biotechnology: Analysis of genomic sequences. Search for genes. Search for patterns within a nucleotide sequence. Proteins and their evolution. Alignment of sequences and similarity matrices. Similarity searches in databases. Analysis of amino acid sequences. Search for patterns within an amino acid sequence. Prediction of the three-dimensional structure of a protein. Models for homology and folding recognition. Computational and visualization techniques for structural bioinformatics. Molecular complex prediction: Molecular Docking. Methods for Docking and Drug Designing. Protein-Ligand Docking methodologies and its applications in Drug Discovery. Concepts and principles of energy calculations. Evaluation of the energy of a molecule. Energy minimization and Molecular Dynamics.
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