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Data integration in systems biology: characterization of biological phenomena from structural and functional information

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(1)

Data integration in systems biology: characterization of

biological phenomena from structural and functional

information

Ronaldo Fumio Hashimoto

Institute of Mathematics and Statists

University of Sao Paulo

Brazil

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Summary

Motivation

Our Approach

Domain Partners

Research Team

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Biological Molecules Interactions

Cell Size Cln3 SBF Sic1 MBF Cln2 Clb5 Cdh1 Clb2 Mcm1/SFF Cdc20/Cdc14 Swi5

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Cell Activity to Data Sets

Replication Transcription Translation

DNA mRNA Proteins Metabolites Organisms

Genomics Transcriptmics Proteomics Metabolomics

Central dogma of biology

Heterogeneous, complex, distributed databases

Various analysis

Data-intensive knowledge discovery

and

systems biology

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Steps for Gene Regulatory Network Inference

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Steps for Gene Regulatory Network Inference

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Steps for Gene Regulatory Network Inference

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Steps for Gene Regulatory Network Inference

Inference Procedure

Cell Size Cln3 SBF Sic1 MBF Cln2 Clb5 Cdh1 Clb2 Mcm1/SFF Cdc20/Cdc14 Swi5

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Tool for Knowlegde Discovery

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number of Variables Small Number of Samples

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number of Variables Small Number of Samples Intrinsic Noise of Expression Measures

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number of Variables Small Number of Samples Intrinsic Noise of Expression Measures Lack Information about the Biological Organism

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number of Variables Small Number of Samples Intrinsic Noise of Expression Measures Lack Information about the Biological Organism High Complexity of Networks

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Challenges of Using Gene Expression Data

Gene Regulatory Network Inference Large Number of Variables Small Number of Samples Intrinsic Noise of Expression Measures Lack Information about the Biological Organism High Complexity Intrisic Error Estimation

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Our Proposal

3 Main Keys Network Topology Incorporation Geographic Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of Attractors

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Our Proposal

3 Main Keys Network Topology Incorporation Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of

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Our Proposal

3 Main Keys Network Topology Incorporation Geographic Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of Attractors

(22)

Our Proposal

3 Main Keys Network Topology Incorporation Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of

(23)

Our Proposal

3 Main Keys Network Topology Incorporation Geographic Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of Attractors

(24)

Our Proposal

3 Main Keys Network Topology Incorporation Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of

(25)

Our Proposal

3 Main Keys Network Topology Incorporation Geographic Small-World Scale-Free Random Data Integration Genomics Transcriptomics Proteomics Metabolomics Other Omics System Dynamics Incorporation Large Basins of Attractions Small Number of Attractors

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Web-Services

Web-Services Faculty of Medicine University of Sao Paulo E. coli Albert Einstein Hospital Sepsis Psychiatry Institute University of Sao Paulo Schizophrenia Autism Brazilian Bioethanol Science and Technology Laboratory Sugar

Cane of BiologyInstitute

University of Sao Paulo

Arabidopsis thaliana

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Research Team

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. André Fujita CMCC-UFABC David Correa Martins Jr. Luiz Carlos da Silva Rozante UTFPR Fabrício Martins Lopes Texas A&M University Ulisses Braga-Neto Edward R. Dougherty IB-USP Marie-Anne Van Sluys Marcos Buckeridge IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

(29)

Research Team

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. André Fujita CMCC-UFABC David Correa Martins Jr. Luiz Carlos da Silva Rozante UTFPR Fabrício Martins Lopes Texas A&M University Ulisses Braga-Neto Edward R. Dougherty IB-USP Marie-Anne Van Sluys Marcos Buckeridge IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. André Fujita CMCC-UFABC David Correa Martins Jr. Luiz Carlos da Silva Rozante UTFPR Fabrício Texas A&M University Edward R. Dougherty IB-USP Marie-Anne Van Sluys Marcos Buckeridge IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

(30)

Research Team

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. André Fujita CMCC-UFABC David Correa Martins Jr. Luiz Carlos da Silva Rozante UTFPR Fabrício Martins Lopes Texas A&M University Ulisses Braga-Neto Edward R. Dougherty IB-USP Marie-Anne Van Sluys Marcos Buckeridge IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

Research Team IME-USP

Ronaldo Fumio Hashimoto Roberto Marcondes Cesar Jr. IPq-USP Helena Brentani Albert Einstein Hospital Julio Cesar Monte FM-USP Carlos Alberto Moreira Filho CTBE Marcos Buckeridge Roberto Marcondes Cesar Jr. TGen Edward R. Dougherty

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Ongoing Research

F. M. Lopes, R. M. Cesar Jr., L. F. da Costa. Gene Expression

Complex Networks: Synthesis, Identification and Analysis. Journal of

Computational Biology, 2011.

F. M. Lopes, E. A. de Oliveira, R. M. Cesar Jr. Inference of Gene

Regulatory Networks from Time-Series by Tsallis Entropy. BMC

Systems Biology, 2011.

C. H. A. Higa, V. H. P. Louzada, T. P. de Andrade, R. F. Hashimoto.

Constraint-Based Analysis of Gene Interactions using Restricted

Boolean Networks and Time-Series Data. BMC Proceedings, 2011.

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References

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