Bioinformatics and Computational Biology
A.Y. 2023/2024
Learning objectives
The course aims to illustrate how computer science principles, technologies, methods and instruments can be profitably used for the computational analysis, information content increment and interpretation of biological data produced by genome sequencing, gene expression measurements and proteomics. It will be highlighted as the application to biological data of the engineering themes of data bases, information theory, data and text mining and others can contribute to increasing biomedical knowledge and improving health care.
Expected learning outcomes
Students will develop biological, bioinformatics and computational skills to manage and process bio-medical-molecular data and knowledge, as well as they will acquire knowledge of the instruments needed to tackle various issues in computational biology; this will make the students able to take advantage of the opportunities offered by the increasing bioinformatics development and relevance.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Lesson period
First semester
Course syllabus
Seminar lectures and practices in informatics room on the following topics compose the course; in case, at the end of the course, an external technical visit to an experimental research laboratory, or a seminar lecture by a field expert, will take place.
- Introduction (2 hours): definitions, methodologies and motivations
- Genetic and molecular biology concepts (8 hours): organisms, cells, biological molecules and their structure, duplication and expression of genetic information, protein synthesis, structure of genes and transcripts, hints of protein structure, genome, transcriptome, proteome, hints of hereditary pathologies
- Techniques of biomolecular sequence analysis (6 hours): importance of biological sequence comparison, local or global alignment of two biomolecular sequences, sequence similarity search
- Technologies for gene expression measurement and analysis (2+4 hours): biotechnologies for gene expression measurement, computational methods for gene expression data analysis, data mining of gene expression data
- Biological network analysis (2 hours): main characteristics of a biological network, mining and visualization of complex network features, computational methods for gene network extraction and analysis, hints of gene regulatory networks
- Bio-terminologies, bio-ontologies and methodologies for their analysis (2+2 hours): functional and phenotypic annotations of genes and proteins, controlled vocabularies for genomic and proteomic annotation, Open Biomedical Ontologies: the Gene Ontology and other bio-ontologies, enrichment and similarity analysis of annotations
- Genomic and proteomic databanks (2 hours): databank types and access methodologies, main databanks and their relations, provided data and formats, search methods in databanks, integration and update of data and information
- Examples of available bioinformatics tools (20 hours): main software tools available as Web applications, Web services and freeware and open source programs
- Introduction (2 hours): definitions, methodologies and motivations
- Genetic and molecular biology concepts (8 hours): organisms, cells, biological molecules and their structure, duplication and expression of genetic information, protein synthesis, structure of genes and transcripts, hints of protein structure, genome, transcriptome, proteome, hints of hereditary pathologies
- Techniques of biomolecular sequence analysis (6 hours): importance of biological sequence comparison, local or global alignment of two biomolecular sequences, sequence similarity search
- Technologies for gene expression measurement and analysis (2+4 hours): biotechnologies for gene expression measurement, computational methods for gene expression data analysis, data mining of gene expression data
- Biological network analysis (2 hours): main characteristics of a biological network, mining and visualization of complex network features, computational methods for gene network extraction and analysis, hints of gene regulatory networks
- Bio-terminologies, bio-ontologies and methodologies for their analysis (2+2 hours): functional and phenotypic annotations of genes and proteins, controlled vocabularies for genomic and proteomic annotation, Open Biomedical Ontologies: the Gene Ontology and other bio-ontologies, enrichment and similarity analysis of annotations
- Genomic and proteomic databanks (2 hours): databank types and access methodologies, main databanks and their relations, provided data and formats, search methods in databanks, integration and update of data and information
- Examples of available bioinformatics tools (20 hours): main software tools available as Web applications, Web services and freeware and open source programs
Prerequisites for admission
No prerequisites different from those required for admission to the Master Degree program
Teaching methods
Class lectures and practices; during course practices, all given in an informatics room using the student's laptop, several bioinformatics technologies, databanks and publicly available tools will be illustrated and used.
Teaching Resources
The slides presented during the course and the estimated detailed schedule of lectures and practices are available on the "Be e-Poli" (BeeP), the portal for the network activities of students and professors at the Politecnico di Milano, accessible from the Politecnico di Milano Web site; students registered to the course for the current academic year can access it.
Assessment methods and Criteria
The assessment is based on a written exam at the end of the course, with exercises and open questions on all the topics presented during the course lectures or practices.
ING-INF/05 - INFORMATION PROCESSING SYSTEMS - University credits: 6
Lectures: 48 hours
Professor:
Masseroli Marco