BRIEF DESCRIPTION



Biology is being transformed into a data-rich science by means of the numerous and significant experimental advances recently obtained through the development of genome sequencing and 'high-throughput' techniques, which are opening completely new avenues of research to unravel the complex mechanisms and interaction networks underlying the extraordinary evolutionary and organizational properties of living organisms. This has lead to the emergence of a novel discipline called 'Systems Biology', combining various ingredients of other fields within the natural sciences, like Molecular Biology, Mathematical or Theoretical Biology, Systems Dynamics and Bioinformatics. The main goal of the present course is, thus, to introduce students to the most basic aspects of this new discipline, emphasizing in particular how the integration of theoretical and experimental strategies can be extremely fruitful and helpful to address some of the most intricate and interesting open questions in Biology.

MAIN OBJECTIVES



A) Introduce students to the subject matter 'systems biology', the motivations behind its emergence as a field of research and its main theoretical/experimental foundations (as well as some conceptual challenges involved).



B) Show students that there are mathematical tools (Dynamical systems theory, Network theory) and specific software (Matlab, Cytoscape, genetic algorithms, cellular automata) through which complex features of biological systems can be grasped and further studied.



C) Favour critical thinking; push students to discuss and debate about those issues of systems biology that are closer to their interests; encourage further reading into specialized literature.



D) Facilitate the acquisition of basic skills in mathematical modelling, as well as the students' elaboration of their own global picture and critical vision of the main research lines in current systems biology -- and other fields akin to it, like synthetic biology.

PROGRAM (I): BASIC THEORETICAL CONTENTS



0. Introduction. 'Systems biology': main motivations and objectives.

1. Is it really possible to define living systems?

2. The problem of origins of life.

3. Self-organization: relevance of the concept for biology.

4. Connection and possible integration of systemic approaches with evolutionary theories.

5. The 'informational' metaphor in biology. Mechanisms of regulation of genetic information.

6. The concept of organism: functional integration and agency. Uni/multi-cellular cases.

7. Biological networks. Examples, classification and applications.

8. Synthetic biology: the challenge of fabricating life. Potential and limitations.

9. Models and description levels in biology: reductionism vs. emergence.





PROGRAM (II): METHODOLOGICAL CONTENTS -- MATHEMATICAL & COMPUTATIONAL TOOLS



i. Introduction to dynamical systems theory

ii. Deterministic methods

iii. Stochastic methods

iv. Matlab practicum -- Brusselator model analysis (B-Z reaction)

v. Network theory: introduction and biological applications

vi. Cytoscape practicum

vii. Main theoretical frameworks for global analysis of metabolic networks:

Introduction to FBA (Flux Balance Analysis) and MCA (Metabolic Control Analysis).

viii. Cellular automata practicum





PROGRAM (III): SEMINARS



a. Proteomics

b. Regulatory Gene Networks

c. Genetic Algorithms

EVALUATION PROCEDURE



Oral presentation of a theme from the subject list (30%) and written essay about it (20%)

(to be carried out in small groups).



Active participation in lectures and seminars (10%).



Practicum reports -- including results to various exercises (20%).



Written exam: answer to one or several theoretical questions and practical exercise or commentary on a short selected text (20%).

• Azken Ebaluazioaren Sistema
• Kalifikazioko tresnak eta ehunekoak:
  • Garatu beharreko proba idatzia (%): 20
  • Test motatako proba (%): 10
  • Praktikak egitea (ariketak, kasuak edo buruketak) (%): 20
  • alde lanak (arazoen ebazpenak, proiektuen diseinuak) (%): 30
  • Lanen, irakurketen... aurkezpena (%): 20

The decision of any student to decline the standard evaluation procedure must be expressed in a written document and in full accordance with our current academic regulations (as a rough estimate: 9 weeks to decline 'continuous evaluation' and 1 month before the end of the lectures --week 11-- to indicate that a student will decline, altogether, the next call for evaluation).

In accordance with our current academic regulations.

Oinarrizko bibliografia

LIST OF BOOKS AND REFERENCES ON THE SUBJECT



- Alon, U. (2007) Introduction to Systems Biology. Chapman & Hall/CRC

- Benner, S.A. & Sismour, A.M. (2005) Synthetic biology. Nature Rev. Genet., 6, 533-543.

- Boogerd FC, Bruggeman FJ, Hofmeyr J-H, Westerhoff, HV (Eds) (2007) Systems Biology. Philosophical Foundations. Amsterdam: Elsevier.

- Fell, D.A. (1997) Understanding the control of metabolism. Portland Press, Londres.

- Kauffman, S. (2000) Investigations. Oxford University Press.

- Keller, E. Fox (2000) The century of the gene. Harvard University Press.

- Kitano, H. (2002) Systems biology: a brief overview. Science, 295, 1662-1664.

- Klipp, E. et al (2011) Systems Biology -- A Textbook. John Wiley & Sons.

- Lewontin, R. (2000) The triple helix: gene, organism and environment. Harvard Univ. Press.

- Maturana, H. & Varela, F. (1987) The tree of knowledge: the biological roots of human understanding. Shambhala Publications, Boston.

- Maynard Smith, J. (1986) The problems of Biology. Oxford: Oxford University Press.

- Oltvai, Z. N. & Barabasi, A. L. (2002) Systems Biology. Life's complexity pyramid. Science 298: 763-764.

- O'Malley, M. A. & Dupré, J. (2005) Fundamental issues in systems biology. BioEssays, 27: 1270-76.

- Voit, E. O. (2012) A First Course on Systems Biology. Garland Science.

Gehiago sakontzeko bibliografia

To be explored.

Aldizkariak

Molecular Systems Biology
BMC Systems Biology
PLoS Computational Biology
IET Systems Biology
Journal of Theoretical Biology
Biological Theory
BioSystems
Theory in Biosciences
Artificial Life
Complexity
BioEssays
Origins of Life & Evolution of Biospheres

Web helbideak

Too many.