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NETWORKSThe Organising Principle of System Biology..
Presented by: Lochana Patar
DBT-AAU Centre
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Complexity of Biological System
Hierarchical organisation of life
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Complexity of Biological System
Metabolites
Genes
Proteins
Moleculesof li fe do not function in
isolation ..
but form complex networks that def ine a
cel l ....
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Why study biology on the level of interacting
and interdependent entities???
Biological Reasons
The function of a gene is NOTspecified in the DNA language
Each gene plays roles inMULTIPLEfunctions
Each function arises from co-operation of MANY genes
Function also depends onimportant properties NOTspecified by genes; epigenetics,properties of water, lipids, self-assembly etc.
Nature has built-in fail-saferedundancy thisONLYemerges at the functional level;
Mathematical Reasons
Combinatorial explosion:suppose a physiological
functions are determinedby 2 genes. With 25000genes 312*106
possibilities.
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System Biology Paradoxical
Approaches
Biology
Technology
Computatio
n
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System Biology??
Starting point for System Biology:
To have a quantitative understanding of the process taking
place in a biological Process.
Aim of System Biology:
To understand the behaviour, dynamics of a biological system.
Heart of System Biology Approach:
An iterative process between laboratory experiments and
mathematical modelling.
Systems biology is characterised as the quantitativeanalysis of dynamic interactionsbetween the
components of a biological system with the aim of
understanding the behaviour of the system as awhole and enabling predictions of its behaviour to be
made. To this end, mathematical concepts areapplied to biological systems so that an iterative
process takes place between laboratory experimentsand computer modelling.
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Main goals of system biology
1. To identity the components that constitute the biologicalsystem;
2. To know the dynamic behaviour of these components (i.e.,how their abundance or activity changes over time in various
conditions); and
3. The interactions among these components
Ultimately, this information can be combined into a model that isnot only consistent with current knowledge but provides newinsights and predictions, such as the behaviour of the system inconditions that were previously unexplored.
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NETWORKS as a Promising tool for
SYSTEM BIOLOGY
Life is a relationship among molecules and not a property ofany molecule
- Linus Pauling
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Basic Network Nomenclature
Networka collection of nodes and links
Nodes represent entities
Links represent interactions between entities
A network can be directedor undirected
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Architectural feature of biological
networks
A. Random Network B. Scale Free Network C. Hierarchical Network
It starts with N nodes and
connects each pair of nodes
with probabilityp.
Number of nodes areconnected randomly to each
other.
the nodes degrees follow a
Poisson distribution, which
indicates that most nodes have
roughly the same number of
links.
These are characterized by a
power-law degree distribution.
The probability that a node is
highly connected is statistically
more significantthan in a random
graph.highly non-uniform, most of
the nodes have only a few links.
A few nodes with a very
large number of links, which are
often called hubs, hold
these nodes together.
scale-free networks could easily
be called scale-rich
The starting point of this construction
is a small cluster of four densely
linked nodes.
This model integrates the scale free
topology with an inherent modularstructure.
It implies that sparsely connected
nodes are part of highly clustered
areas, with communication between
the different highly clustered
neighbourhoods being maintained by a
few hubs.
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Biological Networks are Scale free
Scale free networks are ubiquitous in both biological and technological system.
The origin of the scale-free topology in complex networks can be reduced to two basic mechanisms:
1. Growth Process
2. Preferential attachment
Before duplication
After duplication
B.A.
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Structure of Biological Networks
Organisation of Biological Networks
Transcription factor
Target gene
Components Local level Global level
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Biological networkscontain repeating patterns (local level)
Network MotifPatterns of
interconnections
that recur at
dif ferent parts and
with specif ic
information
processing task
Feed Forward
Motif
`Single input
MotifMultiple input
Motif
Filter noises Co-ordinates noisesIntegrates different
signals
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Network RobustnessRobustnessThe ability of complex systems to maintain their
function even when the structure of the system changessignificantly.
Scale-free networks exhibits robustness.
Tolerant to random removal of nodes (mutations)
Vulnerable to targeted attack of hubs
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Networks in Biology
v
Networks
Nodes
Links
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Yeast Protein Interaction
Networks
It illustrates the disassortativenature
of cellular
networks.
A map of proteinprotein
interactions in Saccharomyces
cerevisiae, which is based on early
yeast two-hybrid measurements.
Links represents a mutual binding
relationship.
It has a feature of scale free
networks.
Colours of the nodes indicates the
phenotypic effect of interactionbetween the corresponding proteins.
Red- lethal
Greennon lethal
Orange- slow growth
Yellow- unknown
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Tools for Network construction and
visualization
This can be done using different software :
CytoscapeCytoscape is an open source software platform for visualizing molecular interaction networks
and biological pathways and integrating these networks with annotations, gene expression
profiles and other state data.
Cell DesignerCellDesigner is a structured diagram editor for drawing gene-regulatory and biochemical networks.
Networks are drawn based on the process diagram, with graphical notation system proposed by Kitano,and are stored using the Systems Biology Markup Language (SBML
GephiGephi is an interactive visualization and exploration platform for all kinds of networks and
complex systems, dynamic and hierarchical graphs.
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Conclusion
Systems biology develops through an ongoing dialog andfeedback among experimental, computational, and theoreticalapproaches.
High-throughput experiments reveal, or allow the inference of,
the edges of global interaction networks. Despite the significant advances in the past few years,
(molecular) network biology is only in its infancy.
Future progress is expected in many directions, ranging from the
development of new theoretical methods to characterize thenetwork topology to insights into the dynamics of motif clustersand biological function.
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References
Barabasi AL, Oltvai ZN (2004). Network Biology:
Understanding the cells functional organization. NatureReviews 5, 101-112.
Albert R, (2007). Network Inference, Analysis and
Modelling in system biology. The Plant Cell 19, 3327-3338.
Chawla K, Barah P, Kuiper M and Bones A, (2011).Sysyem Biology: A Promising tool to study Abiotic stressresponses. Omics and Plant Abiotic stress tolerance, 163-
172.
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Thank you