Systems Biology and Medicine

Dit vak wordt in het Engels aangeboden. Omschrijvingen kunnen daardoor mogelijk alleen in het Engels worden weergegeven.

Doel vak

Course aims:
• Profound insight in the network/multifactorial aspects of disease,
health and function, connecting pathology with the molecular world that
causes or cures the disease
• Profound insight in how an integration of molecular, physiological,
and computational (ICT) techniques can help understand disease, design
therapies and improve biotechnology
• Profound insight in how functional genomics, systems biology and the
integration of environmental data can bring about truly individualized,
personalized or cohort-based medicine, and precision biotechnology •
Efficient introduction to >10 (aspects of) subdisciplines of biomedical
research, by use of corresponding data and by discussing the strengths
and limitations thereof
• Insight in the foundations and paradigms of medical, biological and
exact sciences and in their interactions culminating in systems biology
• Capability of using diverse quantitative methods so as to infer
relevant conclusions through the analysis of data
• Acquaintance with a number of relevant computer programs and precise
experimental methodologies
• Ability to formulate testable hypotheses, to use modelling when doing
this, as well as to amend the hypotheses critically, all based on a
thorough analysis of experimental data in the context of existing
scientific knowledge
• Ability to engage in a critical assessment of the utility and
reliability of data and models
• Ability to analyze critically the state of affairs of the life and
biomedical sciences as well as of bioengineering.

Track ‘Scientific thinking and research’: The students will be
requested to analyze a number of diseases from the network perspective.
Using computer tools and through Jamboree-type discussions students will
research literature data. All aspects of this training line will surface
in this course with the exception of the learning of laboratory
abilities. Track ‘Big data’: Retrieval and use of BIG
DATA, as well as advanced data mining and analysis will be practiced.
Track ‘Mathematical models’: Virtually all aspects will be
addressed; the course will assume that most of these have been met with
previously, but ample time and assistance will be given to the students
to recapitulate them.

Inhoud vak

Networks appear to be crucial anywhere now, be they social networks
(facebook), economic networks (companies), or biological networks
determining health. Most diseases are caused by the malfunctioning of
the networks that determine our health, where many of the latter are
cellular or molecular networks in our body. Type-2 diabetes is for
instance caused by a failing interplay between pancreatic beta cells,
their regulated protein synthesis machinery, the insulin receptor on
peripheral tissues. glucose metabolism in liver, glucose uptake by the
intestine and the microbiota within the later. Similarly, cancer is a
network disease, caused by a variety of alterations in a number of
gene. All too long, medicine has been unable to deal properly with the
multifactorial nature of many human diseases, but in the 2010s multiple
breakthroughs in personalized systems medicine have been achieved or are
in the making. Human bodies are systems (networks of components that
are different from the sum of these components) and it is therefore
systems medicine that is called for.
It is only in the present century that
genomics, functional genomics and systems or network biology have
developed sufficiently to bring about a breakthrough in the
understanding and therapy of disease. The present course familiarizes
its participants with the biological networks that determine the
functioning of the human and associated organisms. This extends from
intracellular molecular networks to the networking of the human with the
microbes in the intestines, vagina, and on the skin. Metabolic as much
signaling and gene-expression networks are involved. The diversity of
network functioning between human individuals as well as between
different individual cells in tumors, is addressed in the course, with
the consequent implications for drug resistance. The course teaches the
student how to approach these networks using simple
bioinformatics and modelling techniques, downloading and then analyzing
data through the wwweb, and arguing in terms of recently discovered
principles that determine network functioning. Furthermore the course
will provide the students with new insights in (a) dominant
multifactorial diseases such as cancer and obesity/metabolic
syndrome/diabetes mellitus, (b) inborn errors of metabolism, (c)
infectious diseases and (d) aging diseases such as Parkinson’s,
Alzheimer’s and Huntington’s. The course will highlight a number of new
methods through which new therapies may be designed, some of which make
the use of experimental animals unnecessary. The course will pay
considerable attention to personalized medicine and nutrition and to the
use of the genome-wide metabolic map therein. The hitherto persistent
separation between ‘Nature’ (the genes) and ‘Nurture’ (nutrition,
lifestyle and environment) will be removed, as will be the barrier
between traditional and modern medicine. The student himself will be
enabled to (i) figure out where in a network the best targets are for
medicinal drugs or other agents to improve network function, (ii) show
why it should be a good idea to target multiple network hubs at the same
and how to determine which, (iii) demonstrate how disease probability
can be predicted somewhat from an individual’s genome sequence, (iv)
show how this might help physicians to come with individual advice with
respect to medicine and nutrition, and (v) experience how functional
genomic, physiological, and dispositional information may be integrated.


Lectures: 18 h
Computer practicals and tutorials: 36 h


Exam with essay questions (50%)
Assignment with report and resulting computer programs (50%):
Interpretation of data with data analysis and the construction of a
Both parts should qualify 5.5/10.

Vereiste voorkennis

Completed first one and a half semester BSc Biomedical Sciences VUA or
UvA (including Pathology and statistics) or equivalent.


Lecture notes with text addressing publications (pdf plus reprint-pdfs)
Lectures' powerpoints
Scientific literature


Optional course for third year BSc Biomedical sciences

Overige informatie

Students with different curricula are welcome after consultation.
The course is also of interest to students interested in precision
biotechnology rather than just precision medicine.

Aanbevolen voorkennis

Interest in application of science in medicine or biotechnology.
Interest in those sciences themselves. Interest in the roles of

Algemene informatie

Vakcode AB_1204
Studiepunten 6 EC
Periode P6
Vakniveau 300
Onderwijstaal Engels
Faculteit Faculteit der Bètawetenschappen
Vakcoördinator prof. dr. H.V. Westerhoff
Examinator prof. dr. H.V. Westerhoff
Docenten prof. dr. J.L. Snoep
dr. B.M. Bakker
dr. D. Molenaar
dr. J.R. Haanstra
dr. J. Lankelma
prof. dr. H.V. Westerhoff

Praktische informatie

Voor dit vak moet je zelf intekenen.

Voor dit vak kun je last-minute intekenen.

Werkvormen Hoorcollege, Computerpracticum

Dit vak is ook toegankelijk als: