Simulating genes operation and Simulating genes operation and interactioninteraction

Rekubratsky V.A., Korotkova M.A.

Cetre “Bioengineering” RASMoscow Physical Engineering Institure (State University)

1. 1. Introducing into the area of Introducing into the area of interestinterest

3

Basic concepts

1. Gene

2. Gene operation

3. Genes interaction

4. Gene network

5. Gene network representation

4

1. Gene

• Hereditary (inheritance) information unit• Defines every organism development

• What does ‘genes operation’ mean?

Organisms development

Genes operation

5

2. Gene operation (gene activity)

Responsible for producing its special protein

Protein amount is the characteristic that can be measured

Production rate varies from cell to cell

What does it depend on?

6

3. Genes interaction

• Some proteins can have positive or negative influence on production rates of other proteins

• This is the way genes can ‘interact’ with each other

• May occur within one cell or throughout a part of organism

7

4. Gene network

• System of gene interactions

• Usually represented by a directed graph:– Vertices represent genes– Arcs represent interaction facts

8

5. Gene network representation

gene B activates gene A (positive interaction)

A B

gene B suppresses gene A (negative interaction)

A B

Real network exampleElementary interactions

9

Importance of study

Organisms development

Genes operation: gene -> protein

Genes interaction (network)

2. 2. Problem statementProblem statement

11

Problems of gene network representation

• No dynamics• No cell localization of interaction processes

• Hard to test• Hard to verify conformity with experimental

data

12

Computer simulation system to be designed:

• Simulates genes operation and interaction in a multicellular organism basing on gene network graph

• Thus verifies conformity with experimental data

13

Computer simulation system to be designed:

• Takes cell localization of interaction processes into consideration

• Enables explicit manipulation of gene operation

CLV1+2

CLV3

WUS

cell division

cell divisionCLV3 CLV1+2

WUSdivision

3. 3. Simulation systemSimulation system

15

Levels of abstraction

gene1gene1gene2

geneM

param1param2

... ...paramN

gene1

gene2

geneM

...

cell vital activity or interaction processes

16

Gene model• Outer state – amount of protein• Inner state – protein generation ability• Speed of protein degradation (gradual decrease of

protein amount)• Block flag – to manipulate gene operation explicitly

Outer state

Inner state

operate

block+

- degradation

17

• Universal mechanism of describing both vital activity and interaction processes

Interaction rules

2. Parameter changes

3. Priority, radius of action,

duration

1. Conditions

Rule of interaction

Interaction processes

- gene interactions,- cell substances transport ...

Vital activity processes

- growth, - division,- tissue differentiation ...

18

Cell group structure

• System’s main orientation is simulation of plant development

19

Cell group structure

• Hemisphere structure is an approximation to plant’s cell group giving birth to the whole upper part of plant

20

Cell group structure

• However, the structure can be used for simulation of many other vital processes in different organisms

21

Simulation flow

• Step-by-step

• Each step corresponds to one cell group state:– cell group structure– cell parameters– gene parameters

4. 4. Program implementationProgram implementation

23

Operation steps1. Setting up gene

network & interaction rules

2. Setting up initial cell group state &

structure parameters

4. Results analysis 3. Simulating, parameters modifying

24

Interface tendencies

• Simplification:– Network creation similar to common drawing– Use of algebraic notation in interaction rule

expressions

• Visual aids– 3D model of cell structure– Graphical indication of simulation flow details– Graphs for cell and gene parameters

25

Extensibility

• Multilevel architecture

• Use of design patterns

• Cross platform– OpenGL– MFC => wxWidgets– Program core (most part of code) is platform-

independent

55. . Test resultsTest results

27

Cell growth and division

28

Gene interaction loop with negative feedback

29

Genetic control of stem growth of Arabidopsis thaliana plant

30

HCV (hepatitis C virus) development and cell infection

66. . NoveltyNovelty

32

System advantages comparing to analogs

• For gene network simulation :– takes cell localization of interaction processes into

consideration

• For all-purpose simulation:– a simpler interface, does not demand programming

skills from a user

77. . ConclusionsConclusions

34

System demonstrates:

• Adequacy to simulate gene network operation in multicellular structures

• Universality to describe large variety of cell interaction and vital activity processes

35

Perspectives and plans

• Development of approaches and algorithms to solve inverse problem

• Transformation into totally cross-platform system

• Further interface simplification

The work is supported by Science & Technology International Park “Technopark

in Moskvorechje” along with “UMNIK” program

Thank you for your attentionThank you for your attention