a knowledge model for analysis and simulation of signal transduction networks
DESCRIPTION
A Knowledge Model for Analysis and Simulation of Signal Transduction Networks. Our project is set up as a collaboration of three departments of Columbia University. Columbia Genome Center Computer Science Department of Medical Informatics. Authors:. Tomohiro Koike, Sergey Kalachikov, - PowerPoint PPT PresentationTRANSCRIPT
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A Knowledge Model for Analysis and Simulation of
Signal Transduction Networks
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Our project is set up as a collaboration of three departments of Columbia University
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Columbia Genome Center
Computer Science
Department of Medical Informatics
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Authors:
Tomohiro Koike, Sergey Kalachikov, Shawn M. Gomez,
Michael Krauthammer, Sabina H. Kaplan,
Pauline Kra, James J. Russo, Carol Friedman,Andrey Rzhetsky
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Ontology:
•collection of concepts
•concept definitions •relationships among concepts•properties of each concept •[explicit axioms]
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Goal – a Particular Application
Problem/Motivation:
Currently a search through the PubMed system with the keywords “cell cycle” and “apoptosis” produced lists of 169,293 and 29,961 articles, respectively.
Clearly it is not feasible to scan all these papers “manually” ...
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Outline of the
system that we
are designing
Relevantkeywords
Pathways
V isula ize
Edit
S im ulate
Com pare
Retrieve collection ofjournal artic les
Save collection ofstatem ent/source
pairs
Natuaral Language Processing
F ilterstatem ents,
resolvecontroversies,
e lim inateredundancies
In s ilicoknock out
or knock ingenes
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Basic concepts
Action, ActionAgent, Process, Publication, Taxon, Disease, Mechanism, Result, Developmental Stage, MicroStructure, State, MacroStructure, Relation, Similarity, RelationType, and ActionTemplate
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We represent a pathway a series of overlapping “links” –
substance/action/substance triplets
Substance A Substance B Substance C Substance D
Representation
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ActionAgent
6. PublicationBook
Article
URL
Database
3. Effect
2. ActionAgent
4. Substance
Protein DNA
RNA
Sm all Molecule
Com plex
Lipid
Carbohydrate
Nucleic Acid
Lipoprotein
Glycoprotein
Glycolipid
Nucleotide
Am ino acid
Gene
Oligonucleotide
Heat shock Cold shock
Osm otic shock Radiation
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Action and Process
1. Action5. ProcessTranslation
Transcription
Apoptosis
Grow th
MovementCell-Cell interaction
Cell-Matrix interaction
Uptake
Killing
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Auxiliary Concepts
Publication, Taxon, Structure, Developmental Stage, and Disease encapsulate pieces of auxiliary information about ActionAgents, Processes and Actions
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Properties of Concepts: ActionAgent
4. Substance:N am e(s)
Publication(s)
3. Effect:N am e(s)
2. ActionAgent:C onceptID
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Properties of Concepts: Action
1. Action:N am e(s)
C onceptIDU pstream ActionAgent(s)
D ownstream ActionAgent(s)C ata lystActionAgent(s)
S ideActionAgent(s)K ineticC onstant(s)
Publication(s)R esult(s)
M echanism
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Duality of actions in signal transduction literature
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Dualism: in the biochemical representation substance A is not a participant of the
action, while it is in the logical representation
Logical Biochemical
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Logic RepresentationBiochemical
Representation Example
A = P I 3KB = A K T /P K B
A = pro te inphospatase 2A
B = FA S -activa ted
serine /th reon inekinase
A = IC EB = C P P 32
A = FA S -LB = FA S
A = (C -M yc:M ax)pro te in com plex
B = cdc25A gene
A = e IF2BB = virtua lly any
gene
A = C a pum pA T P aseB = C a
2+
2+
A
B
A T P
A D P +
(pum p/channe l)
ins ide
B outs ide
-P O4
A
B
(ca ta lyst - phosphatase )
active
B inactive
phosphoryla ted
-P O4
A
B
A T P
A D P
(ca ta lyst - kinase )
active
B inactive
phosphoryla ted
Bactive
C inactive
D +
A (ca ta lyst - pro tease )
A is a ligand
B inactiveA +
active[AB ]B is a receptor
A in itia tes transcrip tion o f B
phosphoryla tion
dephosphoryla tion
transport
c leavage
b ind ing
transcrip tion
transla tion A in itia tes transla tion of B
A activa tes B th rough a processprocess A = FA S -LB = A K T /P K B
A activa tes B th rough an action
other
single action
A
B
"A activates B"
We realized that the
current research literature in molecular biology
Describes pathways on two different levels:
Logical
and
Biochemical
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A activates BA inactivates B
A phoshorylates BA methylates B
...
logical
biochemical
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Both logical and biochemical descriptions can be combined in the same sentence:
Activated raf-1 phosphorylates and activates mek-1.
logicalbiochemical
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Mechanism and Result of an Action
10. Result:C onceptID
Activate:
Inactivate:
8. Disease:N am e(s)
C onceptID
9. M echanism :C onceptID
Bind:S ites
Release:S ites
Modify:S ites
Transport:
CreateBond:N am e
BreakBond:N am e
"Phosphorylate"
"Dephosphorylate"
"Cleave"
"Dem ethylate"
"Rem oveN-Signal"
"BreakCys-CysBond"
"Acetylate"
"Ubiquitinize" "M ethylate"
"M akeCys-CysBond"
"Acylate" "Glycosylate"
"Hydroxylate"
e .g .,
e .g .,
"NucleotideExchange"
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Mechanism and Result
Result LogicalAction
Mechanism BiochemicalAction
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Converting LogicalAction into BiochemicalAction and back
18. ActionT em plate:Nam e
LogicalActionBiochem icalAction
Example:
ActionT emplate:Nam e Phosporylation
LogicalAction:Nam e(s)
Upstream ActionAgent(s)Downstewam ActionAgent(s)
CatalystActionAgent(s)S ideActionAgent(s)K ineticConstant(s)
Publication(s)Result(s)
M echanism
?AB???PublicationActivationPhosphorylate
?ATP, dephosphorylated B, AADP, phosphorylated B , AAATP, ADP?PublicationActivationPhosphorylate
Biochem icalAction:Nam e(s)
Upstream ActionAgent(s)Downstewam ActionAgent(s)
CatalystActionAgent(s)S ideActionAgent(s)K ineticConstant(s)
Publication(s)Result(s)
M echanism
"A phosphorylates and activates B "
1. Action:
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The paper descibing this ontology will appear in Bioinformatics
A. Rzhetsky, T. Koike, S. Kalachikov, S. M. Gomez, M. Krauthammer, S. H. Kaplan, P. Kra, J. J. Russo and C. Friedman, A knowledge model for analysis and simulation of regulatory networks, Bioinformatics, (accepted) (2000).
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Implementation: A Pathway Editor
Koike, T., and Rzhetsky, A. 2000. A graphic editor for analyzing signal transduction pathways. Gene (accepted).
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Human cell cycle/apoptosis pathways
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Small fragment of the same pathway
IL -3
IL -3R
IG F1
IG F1R
IR S 1
R A S
P I 3-K
A K T/P K B
B A D
B cl-XL
FA S -L
FA S
FA DD/MO R T
FL IC E
IC E
C P P 32
apoptos is
m itogen
C yclin D1
pR b
E 2F
C yclin E
P 53
P 21
P 16
P 27
C dk4
P 107
C -Myc
C -Myc
?
B in-1
Max
Max
C dc25A
Max
Mad
Mad
C dk2p
P 27 C yclin E
C dk2p
C yclin E
C dk2 p
C yclin E
C dk2
c ell pro liferation
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O snail,climb Mount Fuji
with no hurry
Issa
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Thank you!