Systems Biology

Mohieddin Jafari
Mar 5th (2018), First Session

Jafarilab.com

Biology in Time and Space

Jafari, M. et al, A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology. PLoS One 12, e0189922 (2017).

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Can A Biologist Fix A Radio?

Lazebnik, Y. (2002). Can a biologist fix a radio, or what I learned while studying apoptosis? Cancer Cell, 2(3), 179-182.

Paradox

The more facts we learn the less we understand the process we study.

Let's Fix A Radio

Testing an approach by applying it to a problem that has a known solution

What makes the difference?

I think it is the languages that these two groups use.

e.g., “a balance between pro- and antiapoptotic Bcl-2 proteins appears to control the cell viability, and seems to correlate in the long term with the ability to form tumors”.

Absence of such language is the flaw of biological research that causes David's paradox.

Biologists & Engineers Tools

Engineers Language Properties

  • Standard
  • Quantitative
  • Common

Arguments (Agree or Disagree?)

  1. Cell is too complex to use engineering approaches
  2. Engineering approaches are not applicable to cells because these little wonders are fundamentally different from objects studied by engineers.
  3. We know too little to analyze cells in the way engineers analyze their systems.

Thinking similar to engineers is a basic requirement for future studies of biologists.

Lazebnik, 2002

“My advice to experimental biologists is to be prepared”

Models and Modeling

  • What is a model?

A model is an abstract representation of objects or processes that explains features of these objects or processes.

  • Purpose and Adequateness of models

A simple but usually forgotten note!

Geroge Box

“Essentially, all models are wrong, but some are useful”

  • Advantages of computational modeling
1. Modeling is cheap compared with experiments.
2. Modeling highlights gaps in knowledge or understanding
3. Modeling can assist experimentation.

Basic Notions for Computational Model

  • Model scope
Which aspects are neglected or simplified?
  • Model statement
Equality or inequality constraints, stochastic processes or probabilistic statements
  • System state
A systems described by its states (state is a snapshot of the system at a given time). A state described by the set of variables that must be kept track of in a model.

Jafari, M. et al, PLoS One 12, e0189922 (2017).

  • Variable, parameters and constants
The quantities in a model (e.g. Avogadro's number, Km or Volume)
  • Model behavior
 (i) Influences from the environment (input)
 (ii) Processes within the system
  • Model classification
Qualitative & Quantitative Models
Deterministic & Stochastic Models
Discrete & Continous Models
Reversibility & Periodicity
  • Steady states(Stationary state or fixed point)
Asymptotic behavior of dynamic systems = the behavior after a sufficiently long time:

1)Steady state 2) Oscillation 3) Chaotic regimes

What is quasi-steady state?
  • Model assignment is not unique
 1) Problem 2) Purpose 3) Intention of the investigator

Networks

The network is a crucial concept in systems biology.

Albert-Laszlo Barabasi

“Reductionism, as a paradigm, is expired, and complexity, as a field, is tired. Data-based mathematical models of complex systems are offering a fresh perspective, rapidly developing into a new discipline: network science.” The network takeover, Nature Physics 2012

Some examples:

  • protein-protein interaction networks
  • protein-RNA interaction networks
  • metabolic networks
  • signaling networks
  • guilt-by-association networks
  • networks connecting gene defects with diseases or diseases with other diseases via common gene defects

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Data Integration

Lowest level of complexity Complex level Next level of complexity
data storage SBML data correlation
data representation CellML Identify biomarker and causative or indicative processes
data transfer SBGN Build and refine dynamic model

Standards

GO - Gene Ontology

SBML - Systems Biology Markup Language

Minimum Information Standards

Model Organisms

  1. Easy handling
  2. Tolerate some degree of variation
  3. Costs
  4. size
  5. lifespan
  6. Important taxonomical properties
  7. Relevance for other species

(Escherchia coli, Saccharomyces cervisiae, Caenorhabiditis elegans, Drosophila melanogaster, Mus musculus)

Popular model organisms for studies of problems in biochemistry and molecular biology

Exercise

Provide 10-15 minutes presentation for:

  1. MIRIAM and MIASE

  2. EcoCyc

  3. CyberCell Database

Further Reading