Lecture 1 - Systems Biology definitions Flashcards

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1
Q

Biology and Medicine - Strange Disciplines

A
  • Biology is the science of living things
  • Categorization, origin & evolution, function
  • Often descriptive and empirical
  • “All of science is either Physics or Stamp Collection” (Ernest Rutherford)
  • Border between life and death ill de”ned
  • Systems Biology: want to make it a quantitative science * But how? and why?
  • What is your view on Systems Biology? What do you expect from this class?
    When we have found how the nucleus of atoms is built up we shall have found the greatest secret of all — except life. (Rutherford)
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2
Q

Time and Space Scales of Life - Consequences

A

1) Life has NO absolute scale in in Space and Time
* There is NO preferred Level of Causation!
* Biological Question determines Level of Causation
2) Life is an emergent property due to molecule interactions
3) Life can only be understood as spatio-temporal dynamic process
Life is an emergent, rather than an immanent or inherent, property of matter. Although it arises from the material world, it cannot be reduced to it.

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3
Q

“Failure” of the Human Genome Project

A

-The Human Genome, the blueprint of life, deciphered in 2001
- No immediate results
-> no simple gene <=> disease relationship
* 2022 - and still searching
-> QTL - quantitative trait locus
-> GWAS: Genome wide association studies
- Why?
-> Genome misses information on object relationships/dynamic interaction -> Systems Biology

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4
Q

What is Systems Biology?

A
  • Usually ill de”ned, many de”nitions abide
    Systems Biology investigates inter- and inner-cellular
    dynamic processes
    using systems theoretic approaches
  • Combination of Systems Theory with molecular biology
    ⇒ ’… not a collection of facts, but a way of thinking’
  • Goal: causative understanding of the molecular principles of life * Uses quantitative data from many sources:
  • Genomics, Proteomics, Databases, Clinical Data
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5
Q

History of Systems Biology

A

JAN SMUTS 1870 - 1950
* General & Prime Minister of South Africa (1919-24,1939-48)
* General und Südafrikanischer Premier * ’Holism and Evolution’ (1926)
* Nature is made up of irreducible parts that cannot be decomposed any further
* ’Holism and Evolution’ (1926)
* The whole and the parts depend on each other.

NORBERT WIENER 1894 - 1954
* Founding father of control theory
* ’Cybernetics or Control and communication in the animal and the machine’ (1948)

LUDWIG VON BERTALANFFY 1901 - 1972
* General Systems Theory of Open Systems
* Derivation of growth laws governing biological systems

MIHAKJO MESAROVIC 1928
Prof. at Case School of Engineering, Ohio.
* Systems Theory and Biology, (1968).
* Argues for systems theory thinking
* First mentioning of Systems Biology in 1968

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6
Q

What is Systems Theory?

A

System (!”! μ% - the connected): a set of interacting or interdependent entities forming an integrated whole.
* Boundaries can by physical and/or logical
* System description independent of physical reality
* similar description for biological, physics, social systems
* Complex system:
system composed out of dierent, interacting parts
* Any complex system has similarities in structure:
* Modularity, Hierarchy, Control
* Provides Insight into the interrelationship of its parts

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7
Q

How does Systems Theory help?

A

SYSTEMS THEORETIC QUESTIONS
- Which signals/pertubations have an impact on the system?
- What can we learn from the stimulus-response of the system?
- What is the significance of differences in system structure?

QUESTIONS OF SYSTEMS BIOLOGY
* How do molecules interact, transmit, store information?
* Which are the cellular pathways?
* How are signals en/decoded?
* What is the role of space and transport?
* How are local decisions transmitted to higher structures?
=> Requires quantitative Data! <=

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8
Q

the Scope of Systems Biology

A

-> Enzymen, Reactions
-> Pathways
-> Cell Functions
- Physiology

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9
Q

Why do modeling?

A
  • Make assumptions explicit
  • Understand essential properties
    -> Understand role of system dynamics, e.g. feedback
    -> Handle complexity
    -> Predict an control
    -> Discover general principles
    ”If you can’t model it, you don’t understand it”
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10
Q

Modeling Approaches II

A

MINING APPROACH (STATISTICAL APPROACH)
-> presence (difference)
-> correlation (covariation)
-> regression (data fit)

SYSTEMS APPROACH (KINETIC MODELING)
-> regression (forecasting)
-> rate equations (state dynamics)

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11
Q

Difference between Systems Biology and Bioinformatics

A

DATA MINING
* Pattern recognition
* Correlation
* Clustering

SYSTEMS APPROACH
* Principles
* Stimulus-response experiments
* Modeling & simulation

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