NELSON David L , COX Michael MI PRINCIPI DI BIOCHIMICA DI LEHNINGER Zanichelli
Harvey Lodish, Arnold Berk, Chris A. Kaiser, Monthy Krieger, Matthew P. Scott, Antony Bretscher, Hidde Ploegh, Paul Matsudaira BIOLOGIA MOLECOLARE DELLA CELLULA Zanichelli
Integrating material supplied by the teacher
Learning Objectives
Knolewdge acquired:
The course offers a deep knowledge of both structure and function of important biomolecules that mediates several basic biologic processes. It also offers the correct perspective for the bioinformatic investigation of system-level processes using modern methods and techniques.
Competence acquired
The student will learn the appropriate methodologies and approaches for the study of biological processes. It will also learn the usage of bioinformatics for data collection and integration.
Skills acquired (at the end of the course):
Use of bioinformatic tools to mine and investigate signalling and metabolic pathways.
Knowledge of important bioprocesses in several types of organisms.
Prerequisites
Knowledge of biochemistry,
molecular biology and cell biology
Teaching Methods
Total hours of the course (including the time spent in attending lectures, seminars, private study, examinations, etc...): 150
Hours reserved to private study and other indivual formative activities: 90
Contact hours for: Lectures (hours): 24 hours
Contact hours for: Laboratory (hours): 12
Contact hours for: Laboratory-field/practice (hours): 12
Further information
Frequency of lectures, practice and lab:
the frequency is strongly suggested.
Teaching tools
The instruments present in the Dipartimento di Scienze Biomolecolari Sperimentali e cliniche –Sez. Scienze Biochimiche are using to perform demonstrative lessons and practice.
Type of Assessment
The exam will be based on an oral colloquium aimed at verifying the knowledge of the topics presented during the course as well as to assess the ability of the student to apply such knowledge to practical and experimental problems.
Course program
Functional analysis of high-throughput data. Recall of biostatistics. Integration systems (genes, transcripts, proteins, metabolites). Genomic, metabolomic, trascriptomic, proteomic and metabolomic Applications. Metabolic and regulatory pathway analysis. Over Representation Analysis. Functional Class Scoring. Topology analysis. Metabolic reconstruction, biomodels and flux analysis.