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Systems Reconstruction TM Technology

Tatiana Nikolskaya, PhD SCO & President, GeneGo, Inc April 22, 2004 Workshop II: Medical Applications and Protein Networks. Analysis of Proteomics Data in the Context of Human Systems Biology. Systems Reconstruction TM Technology. Why Systems Reconstruction?.

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Systems Reconstruction TM Technology

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  1. Tatiana Nikolskaya, PhD SCO & President, GeneGo, Inc April 22, 2004 Workshop II: Medical Applications and Protein Networks Analysis of Proteomics Data in the Context of Human Systems Biology Systems ReconstructionTM Technology

  2. Why Systems Reconstruction? • Avalanche of genomic, gene expression, proteomic, metabolomic data on one hand • Complex human diseases and patient’s data on the other • Understanding of the actual cause of complex diseases on molecular level is still at its infancy • To the HT data mining boils down to statistical analysis • Integration, visualization and data mining of each and every type of HT remains a BIG problem • How to bring different types of molecular and clinical data together? • Systems Reconstruction Technology • Pathway-centered database • Clean and comprehensive content: human cellular pathways • Necessary tools to manipulate each and every type of molecular data • Identified links between pathway elements and human diseases • Ability to retrieve disease-specific pathways • Ability to identify and propose missing/unknown pathways from HT data

  3. MetaCore™ Platform SNP Analysis Tools Importing Tools Network Tools Visualization Tools Pathway Editor Metabolomics Tools Gene Expression Tools: Affy, Agilent, Resolver parsers SAGE analysis tools Proteomics Tools Proprietary Content of 23,000 curated pathway building blocks Novel Database Architecture Oracle Based 150 relational tables

  4. What makes MC special? • The most comprehensive DB of human pathways: • 23,000 human 1-step pathway blocks, rat and mouse orthologs • Vertical integration of pathways: from receptors to core effectors • Extensive manual pathway curation: • Associations with human diseases/conditions • Tissue specificity, sub-cellular localization, effects, mechanisms • >270,000 synonyms resolved • Custom pathway editor to add/change the pathways • Unique database architecture: • Pathways is the backbone for experimental data, literature info • Concurrent mapping of different types of HT data on maps and networks • Multiple time points, treatments/dosages, custom colors, custom ranges • Flexible visualization tools and options: • Mapping of customer’s data on maps and computer-generated networks • Disease- and tissue-specific filters • Tools for expanding and collapsing pathways on networks • User’s choice between data sets and algorithms for generating networks • Tools for reducing overall network’s complexity and expanding it

  5. MetaCoreTM: Content and Capabilities MetaCoreTM, a database of human metabolism and its regulation MetaCoreTM, data-mining tools, algorithms and visualization 23,000 pathway building blocks Metabolic and signaling networks >300 expert-curated maps Rat and Mouse orthologs 270,000synonyms resolved Pathway editor 32,000pathway/disease links Concurrent visualization of HT data 3,250human diseases Affymetrix and Agilent array parsers Transcriptional factors and sites Proteomic and metabonomic parsers 1,200 journals/37,000 unique ref Custom and NCBI SAGE data parser

  6. MC: The Most Comprehensive Database on Human Biology 75% of known human proteins can be visualized on maps and networks

  7. Pathways in MetaCore: Maps and Networks • Interactive, static maps • >300 maps • Signaling, receptors, metabolism • Backbone of formalized “state of art” in the field • Networks of protein interactions • Dynamic; built “on-the-fly” • Exploratory tool • Build new pathways for genes of interest

  8. B C D A Why Manual Curation? Microarray 2D gel Two hybrid screen

  9. 1 2 3 4 5 Projected number of 5-step pathways More than 2,000,000,000 5-step pathways

  10. Maps and Networks Legend

  11. MetaCoreTM: Depth and precision… • transcription • processing RNA • transport PNA from nucleus • stabilization of RNA • translation • 6. Protein transport • 7. Folding & stabilization • 8. allosteric modification • 9. covalent modification

  12. MC: Reconstruction of “Vertical” Pathways from Receptors to Core Effectors

  13. Unique Capabilities: Visualization of Different Types of HT Data within the Same System Gene expression Protein levels Protein Interactions Metabolite concentrations Data parsers link user’s data to relevant molecular objects in MetaCore DB

  14. Concurrent Visualization of Different HT data Agilent Affymetrix Proteomic SAGE

  15. Breast cancer bladder transitional cell carcinoma bladder cancer lung cancer squamous cell carcinoma Borjeson-Forsman-Lehmann syndromecondential cerebellar hypoplasia Alzheimer disease chronic Leukemia breast cancer Alzheimer disease diabetes mellitus Breast cancer Alzheimer disease lung carcinoma Brain tumors adenocarcinoma Tangier disease breast cancer Alzheimer disease colorectal carcinoma breast cancer Cancer Breast cancer Parkinson disease pancreatic cancer glioblastoma Alzheimer disease chronic myelogenous leukemia Wiskott-Aldrich syndrome Alzheimer disease neuroblastoma T cell lymphoma Friedreich ataxia Alzheimer disease Parkinson disease Acute myelogenous leukemia Creutzfeldt-Jakob disease Parkinson disease bladder cancer Alzheimer disease Parkinson disease B-cell chronic lymphocytic leukemia Friedreich ataxia Prostate cancer nephronophthisis 1 Alzheimer disease Lupus erythematosus polycystic kidney disease cystic fibrosis Alzheimer disease squamous cell carcinoma hepatocellular carcinoma Bladder cancer MC : Relevance to Human Diseases

  16. Down-regulated in Glaucoma MC Value: HT Data Mining. Maps Inhibitorsupregulated in Glaucoma

  17. MC value: HT Data Mining. Networks

  18. MC value: Identify Novel Pathways for Your Genes

  19. User Chooses Network-creating Algorithms

  20. Generate Networks From the List of Genes/Proteins. Through Internal transcriptional database

  21. Generate Networks around Single Gene/Protein

  22. Custom Ranges and Colors • Select experiment • Show all descriptions • Add ranges • Switch to indicator state • Select ranges to visualize

  23. Pathway Editor: view/edit Interactions • Search for a protein class • View its interactions • Edit interactions • Edit effect • Edit mechanism • Insert references

  24. Pathway editor: adding new interactions • Search for new interaction’s vertices and their existing interactions • Edit existing existing interactions (if any) or add a new one • Use pull-down menus to specify effect and mechanism (if known) • Add references

  25. Hardware requirement, Maintenance and Upgrades • Server • Oracle 8 DBMS or higher, Apache web server with mod_perl • 2 or more P4/XEON CPU’s with 512-1024 MB of RAM recommended • SCSI HDD is recommended • Linux OS 7.3 (RedHat) • MetaCore™ takes about 300MB of space • Client: • Internet Explorer 6.0 or higher is required • Macromedia Flash 6 (MX) Plug-In is required • P4 CPU and 256MB of RAM is recommended • Maintenance is included in the annual fee • Updates will be shipped quarterly • Web based, easy to use and access

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