Learning objectives
ACQUIRING KNOWLEDGE AND UNDERSTANDING.
Students are expected to acquire a good knowledge of methods for biological sequence analysis and of query sequence and domain databases, and a good familiarity with public databases and software for analysis and results visualization.
APPLYING KNOWLEDGE AND UNDERSTANDING.
Through guided exercises, students will gain the basic skills necessary to face the study of new biological sequences, hypothesizing their function, evolutionary history, structure and localization.
Prerequisites
Students should have a solid background in Biochemistry and Molecular Biology.
Course unit content
1. Biological sequences and databases.
2. Local and global pairwise alignments. Substitution matrices and alignment scores.
3. Methods for query sequences in databases.
4. Analysis of EST sequences.
5. Oligonucleotides design for real-time PCR application.
6. Multiple alignments of protein sequences and their use for functional and structural inference.
7. Creating patterns and profiles from multiple alignments. Query profile, domains and motifs databases.
8. Molecular evolution, phylogeny.
9. Predictions of protein biochemical-structural features. Prediction of intracellular localization. Hydropathy plots and topology of membrane proteins.
Full programme
1. Biological sequences and databases.
2. Local and global pairwise alignments. Substitution matrices and alignment scores.
3. Methods for query sequences in databases.
4. Analysis of EST sequences.
5. Oligonucleotides design for real-time PCR application.
6. Multiple alignments of protein sequences and their use for functional and structural inference.
7. Creating patterns and profiles from multiple alignments. Query profile, domains and motifs databases.
8. Molecular evolution, phylogeny.
9. Predictions of protein biochemical-structural features. Prediction of intracellular localization. Hydropathy plots and topology of membrane proteins.
Bibliography
Key textbook:
“BIOINFORMATICA”, TRAMONTANO Anna, Ed. Zanichelli
Support textbook:
“INTRODUZIONE ALLA BIOINFORMATICA”, VALLE Giorgio-HELMER CITTERICH Manuela-ATTIMONELLI Marcella-PESOLE Graziano, Ed. Zanichelli
Teaching methods
The course is based on classroom lectures aimed to provide the necessary theoretical background, flanked by exercises and specific case-studies/applications in a computer-equipped classroom (1 computer/student) to teach the use of the main softwares utilized for data analysis and visualization.
Assessment methods and criteria
Learning assessment is based on an oral examination, which will be conducted in the form of a presentation of the results obtained and illustrated during the computer classroom exercises, integrated with questions on the specific theoretical background. During the examination, the theoretical knowledge, understanding of the practical exercises and case-studies dealt with during the course, and the ability to apply knowledge and to correctly interpret the results will be evaluated.
Other information
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