| Code |
A004623 |
| CFU |
2 |
| Teacher |
Lorena Urbanelli |
| Teachers |
|
| Hours |
- 14 ore - Lorena Urbanelli
|
| Learning activities |
Affine/integrativa |
| Area |
Attività formative affini o integrative |
| Sector |
BIO/10 |
| Type of study-unit |
Obbligatorio (Required) |
| Language of instruction |
Italian |
| Contents |
The course aims to provide students with the tools to independently use the main primary databases and to understand the functioning and use of the main local, global and multiple alignment similarity search algorithms regarding proteins and nucleic acids |
| Reference texts |
Pascarella, Paiardini “Fondamenti di Bioinformatica”, Zanichelli
Material provided by the teacher |
| Educational objectives |
The course aims to provide students with the tools to independently use the main primary databases containing sequences of genomic DNA, mRNA and proteins, and to understand the functioning and use of the main local (BLAST), global and multiple alignment (CLUSTLW) similarity search algorithms, concerning proteins and nucleic acids |
| Prerequisites |
Basic knowledge regarding the dogma of molecular biology, the amino acid code of proteins, the nucleotide code of DNA |
| Teaching methods |
The course takes place in a computer classroom and is organized as follows: i) classroom lectures relating to the topics included in the program with the aid of slides; ii) practical part consisting of connecting to the databases and programs analyzed during the lesson |
| Other information |
For the calendar of teaching activities and the start and end dates of lessons, consult the DCBB degree course website: www.dcbb.unipg.it/metodologie-per-dotto-e-processo |
| Learning verification modality |
The exam includes a written/practical test lasting approximately 45 minutes which consists of multiple-choice questions and practical exercises based on research and the alignment of sequences |
| Extended program |
Introduction to the course: how bioinformatics was born, the example of consensus sequences and algorithms for analyzing sequences from scratch. Flat-file databases and relational databases. Types of biological databases: nucelotide sequences (genomes, transcriptomes) and amino acid sequences. The determination of the three-dimensional structure of proteins (X-ray crystallography, NMR) and protein structure databases. Nucleotide and amino acid sequences. Similarities and differences in sequence alignment: the problem of the genetic code and the chemical-physical characteristics of amino acid side chains. The dot matrix method. Dynamic algorithms and global and local alignments. Substitution matrices for proteins: PAM and BLOSUM matrices. The concept of "query sequence". The BLAST algorithm. Search exercises for similar sequences using BLASTN. Heuristic algorithms and the dendrogram concept in ClustLW. The limits of current approaches. Practical example of multiple alignments using ClustaLW. Hidden Markov models and their applications: identification of consensus sequences for tarscription factors, identification of leader sequences in proteins. The concept of dominance and motive. The PSSM matrices. Identifying motifs and domains from query sequences. Practical exercise on the Prosite database. Graph theory: nodes, links, hubs. Simple, directed and weighted networks. The adjacency matrix. Single-input, multiple-input, feed-forward, and feedback motifs. Random and scale invariant networks. Practical exercise on the database String. |
