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BIOINFORMATICS (480SM)

A.Y. 2020 / 2021

Professor 
Period 
Second semester
Credits 
6
Duration/Length 
48
Type of Learning Activity 
Related/additional subjects
Study Path 
[PDS0-2018 - Ord. 2018] common
Mutuazione 
Condiviso: SM35 - 480SM - BIOINFORMATICS
Syllabus 
Teaching language 

English

Learning objectives 

The course will provide students with basic knowledge of bioinformatics,
genomics and molecular biology and will develop the following skills
D1. Knowledge and understanding. Understanding of bioinformatics
issues and techniques used for genomic data analysis. Knowledge of
public databases and international standards for the distribution of
genomic data.
D2. Applied knowledge and understanding. Ability to develop, use and integrate different bioinformatics techniques and genomic databases for
the solution of molecular problems.
D3. Autonomy of judgment. Ability to formulate a formal computational
problem from an informal molecular problem.
D4. Communication skills. Ability to express oneself appropriately on
bioinformatics and genomics topics.
D5. Ability to learn. Ability to consult and understand reference texts,
scientific articles and international databases concerning bioinformatics
applications and genomic data.

Prerequisites 

Basic notions of molecular biology, Unix programming and knowledge of
a scripting language.

Contents 

DNA/RNA/proteins. The Central Dogma of molecular biology. Notions of genomics. Bioinformatics databases and applications. Genome browsers and international standards for the distribution and exchange of genomic data. Next generation sequencing. Applications to analyze sequence data. Use of applications to analyze genomic data. Code development for the resolution of genomic problems. Evaluation of the developed code. Bioinformatics pipelines.

The cell. The genome. DNA. Genes. The Central Dogma of molecular biology. Gene expression. Transcription. Translation. The genetic code. Transcripts and RNA. Coding and long non-coding RNA. Proteins. Regulatory regions. Promoters and enhancers. The TATA box. Transcriptome and proteome. Reverse transcription. Repetitive DNA. Mobile DNA. Complexity of the genome. Evolution. Evolution of complexity and the impact of non-coding RNA. Evolutionary importance of transposable elements. Types and families of transposable elements. Impact of transposable elements in diseases. L1 and the human genome. Life cycle of a LINE retrotransposon. Germline and somatic insertions. Transposable element and the brain. Definition of an eukaryotic gene. Mendel's laws. Polymerase chain reaction (PCR) and cloning. Sequencing of genomes. Expressed sequence tags. cDNA libraries. Microarrays. Cap analysis of gene expression (CAGE). Next generation sequencing technologies. RNAseq, DNAseq, ChIPseq. The FANTOM project. The ENCODE project. The 1000 Genomes project. The Geuvadis project. The GTEX project. The Cancer Genome Atlas. Comparative genomics and bioinformatics. Primary sequences databases. Genbank, EBI, DDBJ. Flatfile formats for the distribution of molecular data. Feature table definition. Positional information. FASTA standard format. GFF3 standard format. SAM standard format. BAM standard format. Search engines. Entrez, ENA. Derived databases. RefSeq and UniProt. UniProt search engine. Bioinformatics tools. Similarity searches. How to search for similarity. Local and global alignments. BLAST. Definition of BLAST output. E-value and bit-score. Interpretation of BLAST results. Query, hit, HSP. Different types of BLAST analysis. Fine tuning of the BLAST search. Genome browsers. Genes, transcript and related information in genome browsers. Genome annotation and gene builds. Keep attention to the strand. Biotypes. Tracks in genome browsers. Ensembl, UCSC genome browsers and BioMart. Programmatic access to genome browsers. Best practices on experimental design. Transcriptomic studies. Quality control. Normalization. Filtering. Statistical analysis. Data mining. Importance of replication. Multiple hypothesis correction. Enrichment analysis.

Teaching format 

Lectures and practical exercises in which the problems dealt with and/or
emerged during the lessons are developed and resolved also making use
of active learning methods.

End-of-course test 

For students who follow the course and participate in the practical sessions during the course, a final theoretical/practical test is foreseen. Each student will have to solve a problem inherent the topics covered during the course by developing code that carries out a bioinformatics analysis or each student will have to propose, study, present and discuss a recently published article containing large scale bioinformatics analyzes conducted on functional genomics experiments.

For students who miss more than 30% of the lessons, they could be admitted to the final theoretical/practical test after having passed a written and an oral exam on the topics covered in the course program.

Other information 

.

Texts/Books 

We will mainly refer to the following texts:
V. Buffalo - Bioinformatics Data Skills, Reproducible and Robust Research with Open Source Tool - O’Reilly Media - ISBN-13: 978-1449367374
P. Pevzner, R. Shamir - Bioinformatics for Biologists - Cambridge University Press - ISBN-13: 978-1107648876
B. Alberts et al. - Molecular Biology of the Cell - Garland Science - ISBN-13: 978-0815344643
Other teaching material will be suggested by the teacher during the course.


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