This presentation provides the basic understanding of varous genomics and proteomics techniques.Systems biology studies life as a system .It includes the study of living system using various omic technologies .

1. Systems biology
(integrative biology)
Systems biology is the study of an
organism, viewed as an integrated and
interacting network of genes, proteins and
biochemical reactions which give rise to
life.o (Institute of Systems Biology).
Ultimate goal:to predict de novo biological
outcomes given the list of components
involved. (Genome Institute of Singapore).

2. Systemic perturbation of biological system
Monitoring the pathway responses
Integration of the data
Formulation of mathematical models that
describe the structure of the system &
its response to pertubations.

3. Systems biology : a
network of disciplines

4. System biology view
Figure from Oltvai , Z.N. and Barabasi
Life's complexity pyramid.

5. Interactions between various levels
of biological organization
(from Noble 2008)

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Concepts in systems biology
• System
• Systems thinking
• Complexity theory
• Nonlinear dynamics
• Feedback control
• Robustness
• Emergent properties
• Network

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• Network analysis
I. Network architecture (topology):
1. Microscale
2. Mesoscale
3. Macroscale
II. Network dynamics
• Network topology
• Pathway
• Pathway modularity
• Pathway analysis

8. A FRAMEWORK FOR SYSTEMS
BIOLOGY
Define all of the components of the system.
Systematically perturb and monitor the components.
Reconcile the experimentally observed responses with those
predicted by the model.
Design and perform new perturbation experiments to distinguish
between multiple or competing model hypotheses.
After choosing the set of new perturbations, repeat steps 2
through 4 and iterate.

9. Structure of systems :
Networks
APPROACHES:
1.Bottom up approach
•tries to construct a gene regulatory network
based on the compilation of independent
experimental data
2.Top down approach
•tries to make use of high throughput data

10. SYSTEM BIOLOGY USES VARIOUS
OMIC TECHNOLOGIES TO STUDY
AT DIFFERENT LEVELS

11. GENOMICS
• The branch of molecular biology concerned with the
structure, function, evolution, and mapping of
genomes i.e.study of genome.
• GENOME : the collection of genes contained within
a complete (haploid) set of chromosomes. The
genome is a static information resource with a
defined gene content.

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Overview of microarray
hybridization.

13. DNA SEQUENCING
Commonly used methods :
• Chain termination method
• Maxam and gilberts sequencing method

14. Chain termination method
09/04/15

15. In this process ,four reactin mixtures are set up; each one including:
1.DNA to be sequenced 2.DNA polymerase
3.A supply of nucleotides(A,G,C,T)
4.A small amount of labelled chain
terminating nucleotide :one in each of reaction mixture.
.

16. DNA polymerase synthesise the DNA but incorporation
of terminating nucleotide cause polymerization
to stop.

18. Ending chain at every possible nucleotide position creates a no.
of DNA terminated at same nucleotide but different
positions(shown for 1 reaction mixture)

19. Visualization on gel (from smallest to
largest)

20. If different fluorescent labels are used
sequencing can be done in a single mixture

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22. Maxam gilbert method

24. Pyrosequencing

26. Proteomics
The term proteomics describes the study and
characterization of complete set of proteins
present in a cell, organ, or organism at a given
time .

27. Two-Dimensional Gel
Electrophoresis

28. Mass spectrometry (MS)
• Mass spectrometry (MS) is used to determine
the accurate masses of molecules.
• Mass spectrometry (MS) is an extremely
valuable analytical technique in which the
molecules in a test sample are converted to
gaseous ions that are subsequently separated
in a mass spectrometer according to their
mass-to-charge (m/z) ratio and detected.

29. Components of a mass
spectrometer

30. MS/MS Overview

31. MS/MS Overview

34. MALDI-TOF mass spectrometry
MALDI ionisation mechanism

35. Principle of time-of-flight (TOF)

36. Common proteomic technologies,
applications & limitations

37. Human Genomics and Proteomics Volume 2009, Article ID 239204

38. Phage display library

40. Systems Biology vs. traditional
cell and molecular biology
• Experimental techniques in systems biology are high
throughput;but Intensive computation is involved from
the start in systems biology, in order to organize the data
into usable computable databases.
• Exploration in traditional biology proceeds by
successive cycles of hypothesis formation and testing;
data accumulates during these cycles;while Systems
biology initially gathers data without prior hypothesis
formation; hypothesis formation and testing comes
during post-experiment data analysis and modeling.

41. APPLICATIONS

42. Understanding environment
•Understanding microbes interaction with
ecosystems
• Explain and predict consequences of complex
phenomena such as climate changes
•Recombine various mechanisms within these
diverse organisms to deal with some
extraordinary human problems

43. APPLICATIONS IN FIELD OF
MEDICINE
• In DRUG DISCOVERY
• Understanding complex situations such
as cancer
• Understanding developmental
neurotoxicology

44. CHALLENGES
1.MODELLING CHALLENGES
• Providing the means for checking the constraints and devising
modeling schemes with sound compositional mechanisms;
and
• managing models that may not be consistent with each other,
either across schemes or across scales

45. 2.CHALLENGES IN PROTEOMICS
• Membrane Proteome
• Serum Proteomics and Biomarker
Discovery
3.CHALLENGES IN HANDLING LARGE AMOUNT
OF DATA GENERATED AND COMBINING
THEM TO CREATE NETWORKS
4.SOME TIMES HYPOTHETICAL NETWORKS
GET CREATED