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Overview of Biochemical Pathways

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Title: Overview of Biochemical Pathways


1
Overview of Biochemical Pathways
Academia Sinica Taiwan International Graduate
Program
  • Chun-nan Chi
  • Ph.D. Student of TIGP
  • Academia Sinica
  • cnchi_at_iis.sinica.edu.tw

2
Outlines
  • Biological Backgrounds
  • Study Fields in Biochemical Pathways
  • Competitors
  • Trends of Pathway Research
  • Reference
  • Q A

3
Biological Backgrounds
  • What is Biochemical Pathways
  • Types of Biochemical Pathways
  • How Pathways work Together
  • Why Pathway Studies is Important

4
What is Biochemical Pathways
  • A map of the biological mechanism of an organism

Fig 1. Metabolic Pathways ExPASy,
http//www.expasy.org/cgi-bin/show_thumbnails.pl,
founded by Roche Applied Science.
5
Types of Biochemical Pathways
6
How Pathways work Together
Signal Transduction
1 Glucoses 2 ATP
Metabolism
4 ATP 2 Pyruvate 2 NADH
Regulation
7
Why Pathway Studies is Important
8
Study Fields in Biochemical Pathways
  • Overviews of Pathway Studies
  • Literature Mining
  • Pathway Diagrams
  • Graphical Modelers
  • Pathway Databases
  • Pathway Representation
  • Management Tools for Pathway
  • Database Integration
  • Standard for Exchanging Pathways
  • Pathway Querying Reasoning
  • Simulation

9
Overviews of Pathway Studies
10
Literature Mining
ACTIVATOR activate ACTIVATEE
  • RAF6 activates NF-kappaB.
  • Lck is activated by autophosphorylation at Tyr
    394.
  • Anandamide induces vasodilation by activating
    vanilloid receptors.
  • the activation of Rap1 by C3G
  • the GTPase-activating protein rhoGAP
  • the stress-activated group of MAP kinases

11
Literature Mining
  • Current Methodologies

Text Mining
Alexander S. Yeh et al. (2003) Evaluation of
text data mining for database curation
lessons learned from the KDD Challenge
Cup Bioinformatics, Vol. 19 Suppl. 1 2003, pages
i331i339
12
Literature Mining
  • For more details

Very Good Seminar You shouldnt miss!
Title Literature mining for biomedical
text Speaker Dr. Ting-Yi Sung Date 2004/11/08
Monday 1030 AM 1200 PM Location Auditorium
106 at new IIS Building
13
Pathway Diagrams
  • Static Images of Pathways (Primary)
  • BBID 2001 (Biological Biochemical Image
    Database)
  • The search engine finding the figures on many
    textbooks or journals
  • BPC 2001 (Biochemical Pathway Chart)
  • A poster-liked handmade static image that
    describes the metabolic pathways and cellular /
    molecular processes.
  • BioCarta 2001
  • A database that store the pathway information
    with static image format. Can be browsed by
    categories and searched by keywords. Hosted by a
    commercial company.
  • KEGG 2001 (Kyoto Encyclopedia of Genes and
    Genomes)
  • It is a very famous database that specially
    focuses on storing metabolic pathways
    information. All proteins are categorized in
    their functions by EC (Enzyme Classification)
    Number system.
  • BRIDE 2001 (Biomolecular Relations in
    Information Transmission Expression)
  • It is a binary relation search engine based on
    KEGG database. It can search the binary
    interaction between genes, proteins, or other
    biological molecules.

14
Pathway Diagrams
  • Static Images of Pathways (Minor)
  • SPAD 2001 (Signal PAthway Database)
  • It is a database for genetic information and
    signal transduction pathways. The site is
    unfinished and seems to stop the construction.
  • KMIM 1999 (Kohn Molecular Interaction Map)
  • It is an interaction map for representing the
    network of multi-protein complexes, protein
    modifications, and enzymes for reactions.

15
Pathway Diagrams
  • Dynamic Images of Pathways
  • BioCyc 2002
  • This is a database that contains metabolic
    pathway information for 17 species. It presents
    a pathway chart dynamically.
  • STKE (Signal Transduction Knowledge Environment)
  • This is the site hosted by Science Magazine. It
    collects pathways related to signal transduction
    and is searchable by keywords.

16
Pathway Diagrams
  • Important Papers

Ogata 1998 Computation with the KEGG pathway
database Ogata H, Goto S, Fujibuchi W, Kanehisa
M.Computation with the KEGG pathway
databaseBiosystems. 1998 Jun-Jul47(1-2)119-28.
http//igs-server.cnrs-mrs.fr/ogata/Paper/ogata98
BioSys.html
Karp 2000 The EcoCyc and MetaCyc
databases Peter D. Karp, Monica Riley, Milton
Saier, Ian T. Paulsen, Suzanne M. Paley, Alida
Pellegrini-Toole"The EcoCyc and MetaCyc
databases"Nucleic Acids Research, Vol. 28, No.
1, pp. 56-59http//nar.oupjournals.org/cgi/reprin
t/28/1/56
17
Pathway Diagrams
  • Important Sites for Pathway Diagrams

Metabolic Pathways
Signal Transduction Pathways
18
Graphical Modelers
  • What is the Graphical Modeler?

19
Graphical Modelers
  • Some Graphical Modelers

CellDesigner
BioUML
JDesigner
PathwayBuilder
20
Graphical Modelers
  • Output Format for those Graphical Modelers

21
Graphical Modelers
  • Do we solve the problems for modeling pathways?

Problem 1
  • No graphical modelers can represent different
    knowledge granularities of pathways.
  • No graphical modelers can represent the
    incomplete knowledge of pathways.

Solution 1
  • Use Compound Graph Fukuda 2001
  • Use recursive representation of pathways
    Demir 2002

Fig 2. TGF-ß / Smad Signal Transduction
Pathway Fukuda et al. (2001) Knowledge
Representation of Signal Transduction Pathways.
Bioinformatics, Vol. 17 no.9, 829-837
22
Graphical Modelers
  • Do we solve the problems for modeling pathways?

Problem 2
  • No way to annotate the metadata of a pathway
    for the following information - Species -
    Tissues or Cell Type - Environmental Condition
    (pH, Tempetc.) - Developmental Stage of
    Organism

Fig 3. AKT Signaling Pathway Biocarta,
http//www.biocarta.com/pathfiles/h_aktPathway.asp

23
Graphical Modelers
  • Do we solve the problems for modeling pathways?

Problem 3
  • Hard to represent the following architectures
    of pathways - Pre-conditions Post-conditions
    (Especially for Signal Transduction Pathways
    - Concurrency

Solution 3
  • Petri Net could be a good solution - BioPNML
    (Bio Petri Net Markup Language) - Chen 2003
    Quantitative Petri Net model - Matsuno 2000
    Hybrid Petri Net - Hofestädt 1998
    Quantitative Modeling

Fig 3. An Example of Petri Net Hubert Becker
(2001) Logistik - Ein Überblick (Logistics An
Overview) http//home.t-online.de/home/becker2/pet
rinet.gif
24
Graphical Modelers
  • Do we solve the problems for modeling pathways?

Problem 4
  • No tool has a good representation for modeling
    sequence information including - DNA Sequence
    - RNA Sequence - Protein Sequence

Not Yet!!
Fig 4. DNA Double Strand Structure Ian Stansfield
(2001) Web resources for sequence
analysis http//www.abdn.ac.uk/mbi094/dna.gif
Do we solve the modeling problems?
25
Graphical Modelers
  • What we need to solve the modeling problems?

26
Pathway Databases
  • Most famous metabolic pathway databases

27
Pathway Databases
  • Other metabolic pathway databases

28
Pathway Databases
  • Some signaling transduction pathway databases

29
Pathway Databases
  • Some gene regulatory network databases

DBTBS
SPAD
30
Pathway Representation
  • Can we create a model to represent all the
    situations of pathways?

?
31
Pathway Representation
  • What is a good representation model for pathways?
  • Attributes - List of reactions - Synonyms,
    Species
  • Characteristics - Concurrence - Cyclic -
    Incomplete
  • Types Reactants, Products, Catalysts,
    Inhibitors, Sequences
  • Attributes Synonyms, Location, Concentration,
    other Substrates

Pathway
Substrate
  • Types Synthesis, Degrade, Transport,
    Denatured, Transform, Decomposition
  • Attributes - List of reactants, products,
    modifiers - Conditions before / after the
    reaction - Kinetic Functions (Forward /
    Backward) - Synonyms
  • Types Nucleus, Cytosol, Inner membrane, cell,
    organ, body
  • Attribute Synonyms, Temperature, Size, Local
    Time
  • Characteristics - Pass-thru (e.g.
    trans-membrane)

Reaction
Compartment
Event
Function
Timer
All have the Class-Instance concept
32
Pathway Representation
  • The important papers for pathway modeling
  • Fukuda 2001
  • Compound Graph
  • Demir 2002
  • Incomplete Pathways

33
Pathway Representation
  • How to implement the pathway model?

Relational Database is not enough! We need
stronger relations between entities.
Use Ontology instead!!
34
Pathway Representation
  • What is Ontology?
  • A set of vocabularies and their relationships

Mary
Mary ate an apple
apple
eat
35
Pathway Representation
  • The Compound Graph Fukuda 2001
  • Compound Graph CG (G, T)
  • G Interaction Graph
  • T Decomposition Tree
  • Interaction Graph G (V, EG)
  • V Vertex that represent concepts of knowledge
  • EG Edge in Interaction Graph
  • Decomposition Tree T (V, ET, r)
  • V Vertex that represent concepts of knowledge
  • EG Edge in Interaction Graph
  • r The root node of the decomposition tree T

36
Pathway Representation
  • The Compound Graph Fukuda 2001

Petri Net

Decomposition Tree
Interaction Graph
37
Management Tools for Pathway
  • The well-known Ontology editor
  • Protégé 2000
  • It is a tool which allows user to construct a
    domain ontology
  • It can import the existing ontology with RDFS,
    OWL, or CLIP format.
  • It provides a set of API for developers to
    create their own plug-ins
  • It was developed by SRI (Stanford Research
    Institute)

38
Management Tools for Pathway
  • The screenshot of Protégé 2000

39
Database Integration
  • Current public databases related to pathways

Gene Database
Metabolic Pathways
Signaling Pathways
Regulatory Pathways
Transcription Factors Database
Disease Database
Microarray Database
Protein- Protein Interaction
40
Database Integration
  • What database we are going to integrate?

Gene Symbols
Enzymes
Enzymes
DNA Transcription Factors
Transcription Splicing
Translation Protein Info
41
Database Integration
  • Interesting Problem 1
  • Predict new pathways according the genome
    databases
  • Paley 2002
  • PathoLogic
  • Predict new pathways from a genome database
    based on the known model pathway database
  • Yamanishi 2004
  • Predict new pathways from 4 different genomic
    databases

42
Database Integration
  • Interesting Problem 2
  • Find the sequence of pathways based on Microarray
    database in terms of time

43
Standard for Exchanging Pathways
  • Too many specific file formats to exchange the
    knowledge of pathways

44
Standard for Exchanging Pathways
  • Current famous formats for pathway

45
Standard for Exchanging Pathways
  • What is SBML

System Biology Markup Language
46
Standard for Exchanging Pathways
  • The main structure for SBML

lt?xml version"1.0" encoding"UTF-8"?gt ltsbml
xmlns"http//www.sbml.org/sbml/level2" level"2"
version"1"gt ltmodelgt lt/listOfParametersgt
lt/listOfParametersgt ltlistOfUnitDefinitionsgt
lt/listOfUnitDefinitionsgt ltlistOfCompartmentsgt
lt/listOfCompartmentsgt ltlistOfSpeciesgt
lt/listOfSpeciesgt ltlistOfReactionsgt
lt/listOfReactionsgt ltlistOfFunctionDefinitionsgt
lt/listOfFunctionDefinitionsgt
lt/listOfRulesgt lt/listOfRulesgt
ltlistOfEventsgt lt/listOfEventsgt lt/modelgt
lt/sbmlgt
  • Variables
  • Units
  • Compartments
  • Substances
  • Reactions
  • Functions
  • Rules
  • Triggers

47
Standard for Exchanging Pathways
  • Who is in SBML Project?

48
Standard for Exchanging Pathways
  • Advantages of SBML
  • Good for quantitative analysis
  • Good for simulation
  • Disadvantages of SBML
  • Can not represent the following relationships
    between reactions (Which is bad for representing
    pathways)
  • Sequential Relationships
  • Conditional Branch
  • Iterative Relationships

49
Standard for Exchanging Pathways
  • How many tools support SBML?

50
Standard for Exchanging Pathways
  • What is BioPAX

Biological Pathways Exchange
51
Standard for Exchanging Pathways
  • Application of BioPAX

52
Standard for Exchanging Pathways
  • The Classes Hierarchy of BioPAX

53
Standard for Exchanging Pathways
  • Who is in BioPAX Project?

54
Standard for Exchanging Pathways
  • Advantages of BioPAX
  • Good for pathways knowledge management
  • Good for qualitative inference
  • Disadvantages of BioPAX
  • Only support metabolic pathways
  • No quantitative information can be stored in
    BioPAX

55
Standard for Exchanging Pathways
  • How many tools can support BioPAX
  • Protégé 2000 with the OWL Plug-in

56
Standard for Exchanging Pathways
  • Roadmap of BioPAX

57
Pathway Querying Reasoning
  • Basic Queries

Protein Name
Protein Sequence
Neighborhood Navigation
Route Suggestion
58
Pathway Querying Reasoning
  • Some reasoning examples

59
Pathway Querying Reasoning
  • Other reasoning idea 1 Find all crosstalk
    pathways in a specific cell type
  • Given a set of genes, tell me all the pathways
    that will influence these genes including
    following information
  • Species
  • Cell line / Cell type
  • From what tissue?
  • From what age of the organism?
  • Treatment
  • Reacting period
  • All crosstalk pathways of the candidate pathways

Literature Mining
Time-course Microarray Data
Computational Method
60
Pathway Querying Reasoning
  • Other reasoning idea 2 Pathway Construction
    Helper

Pathway Database
A ? C
61
Simulation
  • Why simulation?

62
Simulation
  • Previous works in Simulation
  • Simulate the Kinetics of Biochemical Metabolic
    Pathway
  • METAMODEL (Cornish-Bowden and Hofmeyr, 1991)
  • Contain up to 20 reactions (enzyme) and up to 30
    metabolites as well as its concentration
  • SCAMP (Sauro, 1993)
  • A general purpose simulator of metabolic and
    chemical networks
  • GEPASI (Mendes, 1993, 1997)
  • Simulate the kinetics of biochemical reactions
  • KINSIM (Barshop et al., 1993 Dang Frieden,
    1997)
  • Good tool to simulate the Kinetics of
    biochemistry
  • MIST (Ehlde Zacchi, 1995)
  • A software package which can be used for dynamic
    simulations, stoichiometric calculations and
    control analysis of metabolic pathways

63
Simulation
  • Previous works in Simulation
  • Simulate Gene Regulation Expression
  • Meyers and Friedland, "Knowledge-based simulation
    of genetic regulation in bacteriophage lambda",
    Nucleic Acids Research, January 1984
  • K. Koile and GC Overton. "A qualitative model for
    gene expression." In Proceedings of the 1989
    Summer. Computer Simulation Conference, pages
    415-421, 1989
  • Peter D. Karp(1993), "A Qualitative Biochemistry
    and Its Application to the Regulation of the
    Tryptophan Operon"
  • Arita, M., Hagiya, M. and Shiratori, T. (1994),
    "GEISHA SYSTEM an environment for simulating
    protein interaction"
  • McAdams and Shapiro (1995), "Circuit Simulation
    of Genetic Networks", Science, 269, 650-656

64
Simulation
  • Previous works in Simulation
  • Simulate Cell Division Cycle
  • Tyson,J.J. (1991), "Modeling the cell division
    cycle cdc2 and cyclin interactions"
  • Novak,B. and Tyson,J.J. (1995), "Quantitative
    analysis of a molecular model of mitotic control
    in fission yeast
  • Simulate Signal Transduction Mechanisms
  • Bray D, Bourret R B, Simon M I. Computer
    Simulation of the Phosphorylation Cascade
    Controlling Bacterial Chemotaxis., Molecular
    Biology of the Cell. VOL.4, PAGE.469-482 (1993)

65
Simulation
  • Previous works in Simulation
  • The whole cell simulation

66
Competitors
  • Peter Karp (USA)
  • Minoru Kanehisa (Japan)

67
Peter Karp (USA)
Peter D. Karp Director Bioinformatics Research
Group Artificial Intelligence Center Stanford
Research Institute
68
Minoru Kanehisa (Japan)
Minoru Kanehisa (?? ?) Director Bioinformatics
Center Institute for Chemical ResearchKyoto
University
69
Trends of Pathway Research
  • DB Represent.
  • Integration
  • Exchange
  • Text mining
  • Graphical Modeler

Pathway Database
Annotation
Data Acquisition
Mechanism Understanding
Function Prediction
Re-annotation
DB Management
  • Mngmt. Tools
  • Inference

Ouzounis CA, Karp PD. (2002) The past, present
and future of genome-wide re-annotation. Genome
Biol. 20023(2)COMMENT2001. Epub 2002 Jan 31.
70
Reference
  • Alexander S. Yeh et al. (2003) "Evaluation of
    text data mining for database curation lessons
    learned from the KDD Challenge Cup"
    Bioinformatics, Vol. 19 Suppl. 1 2003, pages
    i331i339
  • Ogata H, Goto S, Fujibuchi W, Kanehisa
    M."Computation with the KEGG pathway
    database."Biosystems. 1998 Jun-Jul47(1-2)119-28
    .
  • Peter D. Karp, Monica Riley, Milton Saier, Ian T.
    Paulsen, Suzanne M. Paley, Alida
    Pellegrini-Toole"The EcoCyc and MetaCyc
    databases"Nucleic Acids Research, Vol. 28, No.
    1, pp. 56-59
  • Ken-ichiro Fukuda and Toshihisa Takagi,
    "Knowledge representation of signal transduction
    pathways." Bioinformatics, Vol 17, No. 9, 2001
  • E. Demir, O. Babur, U. Dogrusoz, A. Gursoy, G.
    Nisanci, R. Cetin-Atalay, M. Ozturk, "PATIKA an
    integrated visual environment for collaborative
    constrcution and analysis of cellular pathways."
    Bioinformatics, Vol. 18 no. 7 2002, Pages
    996-1003
  • Natalya Fridman Noy, Ray W. Fergerson, Mark A.
    Musen, "The Knowledge Model of Protege 2000
    combining interoperatability and flexibility."
    2th International Conference on Knowledge
    Engineering and Knowledge Management (EKAW'2000),
    Juan-les-Pins, France, 2000.
  • Yoshihiro Yamanishi, Jean-Philippe Vert, Minoru
    Kanehisa, "Protein network inference from
    multiple genomic data a supervised approach."
    Bioinformatics, Vol. 20, Suppl. 1, 2004, pp.
    i363-i370
  • Suzanne M. Paley, Peter D. Karp, "Evaluation of
    Computational Metabolic-Pathway Predictions for
    Helicobacter pylori." Bioinformatics, Vol. 18,
    no. 5, 2002, pp. 715-724
  • Ouzounis CA, Karp PD. (2002) The past, present
    and future of genome-wide re-annotation. Genome
    Biol. 20023(2)COMMENT2001. Epub 2002 Jan 31.
  • Tomita,M., Hashimoto,K., Shimizu,T.S.,
    Matsuzaki,Y., Miyoshi,F., Saito,K., Tanida,S.,
    Yugi,K., Venter,J.C. and Hutchison,III,C.A.
    (1999)"E-CELL software environment for
    whole-cell simulation."Bioinformatics, 15, 72-84
  • Schaff,J.C. and Loew,L.M. (1999) "The virtual
    cell" In Altman,R.B., Dunker,A.K., Hunter,L. and
    Klein,T.E. (eds), Pacific Symposium on
    Biocomputing, volume 4, World Scientific,
    Singapore, pp. 228-239

71
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