Master's Degree in Bioinformatics for Computational Genomics
Milan, Italy
Master degree
DURATION
2 years
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
EARLIEST START DATE
TUITION FEES
STUDY FORMAT
On-Campus
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Key Summary
The Master Degree in 'Bioinformatics for Computational Genomics' (BCG) aims to form graduates with an adequate knowledge about the molecular basis of biological systems; the structure and function of biological molecules and how they participate in cellular processes; the technologies and platforms for the analysis of genomes; the tools for bioinformatic and genomic analysis; and the statistical and computational methodologies for the analysis of biomolecular data.
The BCG degree therefore includes activities providing in depth knowledge on:
1. the organization of information in the genome and the molecular and cellular processes at the basis of gene expression and its regulation
2. the experimental methods used for studying genes and their function in different model species, both prokaryotic and eukaryotic
3. the technologies employed in modern genomic research
4. methods and protocols of bioinformatic analysis in functional genomics studies
5. algorithmic, mathematical and statistical approaches underlying bioinformatic and genomic analysis tools
6. data base technologies for the storage and organization of the data
7. modelling and analysis techniques employed in systems biology for the study of interactions in complex biological systems.
The program includes, as a fundamental step in the formation of the students, an internship in research laboratories either at the University of Milan or in other Italian or foreign research institutes. The research experience of the internship and its results will be described in a final written dissertation, to be discussed in front of a thesis committee.
1st Course Year
1st Semester
- Bioinformatics and Computational Biology
- Organic Chemistry
2nd Semester
- Biostatistics
- Genomics and Transcriptomics
- Machine Learning
- Scientific Programming
Elective Courses
Students with a Degree/Background in Computer Science, Engineering, Mathematics, or Physics (Knowledge Alignment Plan 1)
- Biochemistry
- Genetics, Cellular and Molecular Biology
Students with a Degree/Background in Life Sciences (Biology or Biotechnology or Equivalent) (Knowledge Alignment Plan 2)
- Programming and Databases
- Statistics
2nd Course Year
1st Semester
- Advanced Genomics and Epigenomics
- Structural Chemistry
2nd Semester
- Systems Biology and Network Analysis
Further Elective Courses
- Open Choice Courses: 12 CFU
- Genomic Big Data Management and Computing
- Interdisciplinary Project
- Neurogenomics and Brain Disease Modelling
Knowledge and Understanding
Graduates in BCG will acquire an in-depth knowledge allowing them to apply a multidisciplinary and computational approach to solving complex problems in the fields of biology and biotechnology. The degree aims at providing integrated knowledge of different fields of chemistry and biology, which represent the foundations for a Master's degree in the class of Biotechnology. The BCG Master's degree aims in particular to provide solid interdisciplinary knowledge for the development and application of computational tools for bioinformatic and genomic analysis.
Applying Knowledge and Understanding
A fundamental objective of the Master's degree in BCG is to provide students with the ability to apply the knowledge acquired. This aim will be achieved both with class contents and with the final internship in a research laboratory. Suitable teaching time will thus be devoted to problem-solving and activities that will augment the analytical and methodological skills of the students. The skills acquired in classes on fundamental topics will be applied to the design and development of bioinformatic tools for genomic, transcriptomic, epigenomic, and systems biology studies.
Autonomy / Judgment (Making Judgments)
The acquisition of autonomous skills for making judgments will be made possible by the teaching methods employed in classes and the respective topics. The latter ones will often refer to relevant problems and research lines in different areas and will include problem-solving activities that will take place during classes or the development of projects to be discussed at exams. The usage of teaching material alternative to textbooks (research articles, online tutorials, and videos) will be encouraged, in order to make students acquire notions with a proactive and autonomous approach.
Communication Skills
Communication skills can be defined as the acquisition of tools and knowledge for scientific communication using the English language; skills in computing for the elaboration, presentation, and discussion of experimental data; being able to work autonomously, and being able to communicate the results of one's activities to others in seminars, journal clubs, etc. The acquisition of these skills will be included in classes and in the experimental laboratory activities leading to the final dissertation (reading and discussion of scientific literature; reading and discussion of analysis protocols; elaboration and discussion of experimental data).
Learning Skills
Learning skills can be defined as the development of suitable skills for the acquisition of novel knowledge, also through retrieval and study of scientific articles in English or access to databases and retrieval of information. These skills will be acquired during the experimental laboratory activities leading to the final dissertation, or the reading and discussion of scientific literature during classes or exams. These activities will allow students to learn through a 'hands-on' approach and through constant interaction both with their peers and the instructors.
The BCG Master's degree aims to train highly skilled professionals able to merge in-depth knowledge of the molecular foundations of life sciences with up-to-date knowledge of the current techniques and technologies for bioinformatic and genomic analysis. Particular emphasis will be put on the quantitative and computational aspects of the latter, which will be focused on the analysis, modeling, and comprehension of biological systems. The ultimate goal is to train in a multidisciplinary context professionals ready to cope with the challenges deriving from modern biomolecular sciences in the postgenomic era, and able to conjugate and integrate knowledge on biology, genetics, computer science, information engineering, and statistics in different fields of basic or applied research. The BCG program aims to train the following professional figures: biologist and related figures, biotechnologies.
Graduates in BCG Will Be Able to:
- Take part in the design and execution of large-scale genomic analyses
- Identify and extract the biological meaning from the results obtained
- Design autonomous tools and protocols for the bioinformatic analysis of different types of experimental data
- Play a pivotal role in research groups focused on basic or applied genomics research
- Coordinate and supervise research projects and groups focused on bioinformatics and genomics