Advanced Topics in Bioinformatics
This curricular unit aims at giving a general overview of the major areas of Bioinformatics and Chemoinformatics, providing the students with knowledge on the fundamentals as well as on practical applications in biosciences. The knowledge and skills acquired in this curricular unit will allow the students to have a general understanding of the scientific literature in the area, to be able to (individually) deepen their knowledge in selected areas in bioinformatics, and to use some computational tools to study real‐life problems in biosciences.
Cláudio Manuel Simões Loureiro Nunes Soares, João Montargil Aires de Sousa
Weekly - 5
Total - 56
Basic computer skills.
1. Leach, A. R., Molecular Modelling: Principles and Applications, 2nd ed., Prentice Hall, 2001
2. Bioinformatics and Molecular Evolution by Paul G. Higgs and Teresa K. Attwood. Wiley-Blackwell (ISBN-13: 978-1405106832)
3. An introduction to systems biology. Design Principles of Biological Circuits. U. Alon. Chapman & Hall/CRC Mathematical & Computational Biology; 2006.
4. Chemoinformatics - a Textbook, Gasteiger, J. Engel, T., Eds.; Wiley-VCH: Weinheim, 2003.
5. Leach, A. R.; Gillet, V. J. An Introduction to Chemoinformatics, 2ª ed.; Springer: Dordrecht, 2007.
6. Handbook of Chemoinformatics: from Data to Knowledge, Gasteiger, J., Engel, T., Eds.; Wiley-VCH: Weinheim, 2003.
7. Key papers from diverse fields.
Classes will be Lectures/problem-solving with computers.
Evaluation consists of class evaluation (50%) and final test/exam (50%). Class evaluation will be based on a computational work. A minimum grade of 9.5 is required in the final test/exam to be approved.
Evaluation consists of class evaluation (50%) and final test/exam (50%). Class evaluation may be based on a computational work. A minimum grade of 9.5 is required in the final test/exam to be approved.
1) Computational genomics and evolution.
2) Computational systems biology.
3) An experimentalist survival guide in computational biology methods – Practical sessions, in a problem solving context.
4) Representation and visualisation of molecular structures.
5) Introduction to molecular mechanics/dynamics.
6) Molecular docking.
7) Protein structure prediction
8) Quantitative Structure‐Activity Relationships (QSAR).
9) The role of Chemoinformatics in drug discovery and development
Programs where the course is taught: