Universitat Internacional de Catalunya
Bioinformatics
Other languages of instruction: Catalan, Spanish
Teaching staff
Students are requested to email to arrange a meeting.
Dr Pau Marc Muñoz Torres (pmunoz@uic.es)
Introduction
Bioinformatics is an area of research where computer science and information technology are applied for the treatment of biological data. This is inherently cross-disciplinary. It is applicable to all areas of the life sciences and health, including genomics, proteomics and gene and metabolic networks. The fields on which it has a key impact are very diverse and increasingly specialized, which makes bioinformatics a rare and highly valued profession. The sheer volume of data that different biomedical fields generate necessitates the use and development of computational techniques, making bioinformatics an essential science and leading to the transformation of this avalanche of data into knowledge. To manage all this information flexibly and naturally represents one of the greatest current challenges, ranging from the bioscience design of databases and algorithms for storing and analysing the information and networking models that integrate all available information.
Pre-course requirements
None.
Objectives
- To identify the different areas that includes the word "bioinformatics".
- To understand and to manipulate the molecular main public data bases.
- To introduce the in-silico design of biomolecules
Competences/Learning outcomes of the degree programme
- CB10 - Acquire learning skills that allow them to continue studying in a self-directed and autonomous mode.
- CB6 - Knowledge and understanding to provide a basis or opportunity for originality in developing and / or applying ideas in a research context.
- CB7 - To apply the acquired knowledge, and develop their ability to solve problems in new environments within broader (or multidisciplinary) contexts related to their field of study.
- CB8 - Integrate knowledge and deals with the complexity of formulate judgments based on scientific evidence, from information that may be incomplete or limited, include reflecting on social and ethical responsibilities linked to the application of their knowledge and judgments.
- CB9 - Communicate findings, knowledge and reasons to present to specialists and non-specialists in a clear and unambiguous.
- CE10 - Know how to apply the epistemological, ethical, legal and humanitarian exercise in research and dissemination of results.
- CE4 - Apply experimental animal models as well as the methodology of animal handling and ethical concepts in research in dentistry.
- CE9 - Apply the latest technological advances in dental research, considering its properties, indications, biocompatibility, toxicity and environmental impact.
- CG1 - Ability to integrate new knowledge through research and study, and deal with complexity
- CG2 - Ability to review analysis and discussion of the experimental results and to issue the corresponding conclusions.
- CG3 - Self learning ability in the development of new techniques, in the knowledge of new scientific concepts and in the search of new scientific information
- CG4 - Ability to argue and defend own scientific ideas and listen, analyze, evaluate and respond to the ideas of another person.
- CT1 - Ability to work in multidisciplinary and multicultural groups
Learning outcomes of the subject
- Properly designed experimental / non-experimental studies and knowledge of the basic principles of qualitative studies.
- Aware of the latest advances in the field of interest chosen.
- Integra experimental research with care and treatment possibilities.
Syllabus
Chapter 1 GENOMICS
1.1 Techniques for next generation sequencing and analysis of the data produced : from assembly to annotation and functional analysis.
1.2 Variation present in the genome: nucleotide variation and structural variation
1.3 Genome browsers.
1.4 Association studies linking genetic variation with phenotype.
1.5 Bio-information analysis tools (similarity search and multiple sequence alignment) and their implementation.
Chapter 2 PROTEOMICS
2.1 Basics of structural biology.
2.2 Common strategies in protein analysis: identification and study or prediction of the structure.
Chapter 3 SYSTEMS BIOLOGY
3.1 Study of networks and use of models.
Teaching and learning activities
Online
Teaching: CM, MC, TRB
Learning activities: CT (1 ECTS)
Evaluation systems and criteria
Online
Continuous evaluation - EC (20%)
Case study work - RC (30%)
Final exam - PFE (50%)
Bibliography and resources
Provided by the teacher