Bioinformatics and Systems Biology
Basics of general, inorganic, and organic chemistry.
KNOWLEDGE AND UNDERSTANDING:
The course is aimed to apply the computational tools, algorithms and theoretical methods of bioinformatics and computational biology for modeling, mining, and analyzing biological systems: from the single biomolecule to the complex biological networks.CAPACITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
This course, mandatory for the master students, allows to learn the basic concepts of biology and biochemistry that are fundamental for the use of computational techniques applied to scientific research in the biomedical and biological complex systems (genomics).
The student will also acquire necessary critical skills to be able to select and combine, among the acquired bioinformtics tools, those needed to undertake novel and complex computational tasks requested in the work envinronment.TRANSVERSAL SKILLS:
The integration of bioinformatics knowledge with in-depth knowledge of chemistry, biochemistry and molecular biology delivered within this course will provide added value to the preparation of students of Bioinformatics and Systems Biology. In particular, students will acquire the ability: 1) to interface and integrate in a multidisciplinary work and research team involving research in "wet lab"; 2) to make "predictions" that can be directly tested in laboratory; 3) to support or refute, from a computational standpoint, experimental researches already in place.
Elements of comparative biochemistry. Elements of comparative Molecular Biology. Introduction to Bioinformatics. Functional genomics. Biological Databases and databanks. Name and function of database. Retrieval of data and its description. Gene expression analysis. Pairwise sequence alignments. FASTA and BLAST. Multiple Sequence Alignments. Methods of Gene prediction. Sequence Similarity networks. Comparative genomics. Methods for discovery and characterization of sequence motifs. Phylogenetics and Evolutionary Bioinformatics. Molecular modeling of proteins: from simulation to drug design applications. Introduction to Synthetic and Systems Biology.
Development of the examination
LEARNING EVALUATION METHODS
The learning evaluation of the students is carried out by an oral test, which may include a brief written test, depending on the assigned tasks.
LEARNING EVALUATION CRITERIA
To successfully pass the exam, the student must properly address 2-3 questions which will include up to one question related the Biochemistry and Molecular Biology background sections of the course.
LEARNING MEASUREMENT CRITERIA
Attribution of the final mark up to thirty
FINAL MARK ALLOCATION CRITERIA
The final evaluation is positive if the student obtains at least eighteen out of thirty allocated points. The highest rating is achieved by demonstrating a deep understanding of the course content. Cum laude is given to students who have demonstrated a particular brilliance in the exposition.
Given the multidisciplinary nature of the course, no specific textbook is recommended. Students will be provided references to web material or other sources to deepen the subjects illustrated over the course lessons.
- Biomedical Engineering (Corso di Laurea Magistrale (DM 270/04))