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B024458 - COMPUTATIONAL BIOCHEMISTRY
Main information
Teaching Language
Course Content
Suggested readings
Learning Objectives
Prerequisites
Teaching Methods
Type of Assessment
Course program
Academic Year 2018-19
Course year
Third year - First Semester
Belonging Department
Experimantal and Clinical Medicine
Modulo di sola Frequenza of
Scientific Area
BIO/10 - BIOCHEMISTRY
Credits
3
Teaching Hours
24
Teaching Term
01/10/2018 ⇒ 30/04/2020
Attendance required
No
Type of Evaluation
Giudizio Finale
Course Content
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Course program
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Lectureship
Teaching Language
Italian
Course Content
Theory and practicals on biological sequence analysis, Pairwise and multiple alignments. Scoring matrices and modelling of multiples equence alignments. Biochemical and biological pathways, system processes and related investigation methods.
Suggested readings (Search our library's catalogue)
Fondamenti di bioinformatica - Krane e Raymer
Introduction to Bioinformatics - Lesk
Course material
Introduction to Bioinformatics - Lesk
Course material
Learning Objectives
The course aims at providing the main notions of computational themes related to the biochemical analysis. Specifically, the student will earn the theory of protein sequence comparison and the formation of the concept of protein families, that will be further consolidated by showing methods and procedures for their application in the analysis of cellular metabolic and signaling pathways. Such notions represent the state-of-the art in biotechnology and represent an innovative learning goal for students.
Prerequisites
Notions of biochemistry and molecular and cellular biology
Teaching Methods
Frontal lessons with available course material.
Type of Assessment
Oral examination in the presence of the three teachers of the Computational Biochemistry and Biology, aimed at verifying the completeness of the notions as well as the ability of the student of integrating the novel computational concepts to the previous knowledge of biochemistry and cell biology. The student will be also asked to propose a -omic experiment and describe its methods and expected results.
Course program
Analysis of biological sequences. Similarity search. Pairwise alignmetn methods (exhaustive and euristic). Multiple alignments and domain profiles. Positional scoring matrices and Markov models. Search by functional domains. Main data banks in functional biochemistry. Types of cell communication. Intra-extra cellular signals and their sensing. Signaling pathways: sequential cascades and physical associations. Cell proliferation: phenomenon and potential hubs. Cell motility: phenomenon and potential hubs. Apoptosis: phenomenon and potential hubs.