Sys-Bio Gateway: a framework of
bioinformatics database resources
oriented to systems biology
http://www.itb.cnr.it/sysbio-gateway
Milanesi Luciano
National Research Council
Institute of Biomedical Technologies, Milan, Italy
luciano.milanesi@itb.cnr.it
Luciano Milanesi 14-15 September 2009, Edinburgh
Outline
• Introduction
• Methods for data integration and data analysis
• SysBio-Gateway
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Cell Cycle Database
G2S Breast Cancer Database
Nervous System
Kinweb
ProCMD
TMA Rep
• Conclusion and Acknowledgments
Luciano Milanesi 14-15 September 2009, Edinburgh
System Biology for Health
Luciano Milanesi 14-15 September 2009, Edinburgh
Data Integration
• Definition of data integration:
the process of combining information, residing at different
resources, to provide the user with a unified view of these
data for enabling the possibility to achieve real knowledge
.
U.I.
Workflow
Jobs
HPC
Grid
Soap
Results
Luciano Milanesi 14-15 September 2009, Edinburgh
Data Integration
• Data integration is an essential task to accomplish in order
to achieve a view of the biological knowledge as much
complete as possible in emerging fields such as
bioinformatics and systems biology.
• The integration of biological knowledge in the systems
biology field is related to different levels, such as
genomics, transcriptomics, proteomics and network
interactions.
• Such data integration is crucial in order to support the
mathematical modelling and the computer simulation of
biological pathways
Luciano Milanesi 14-15 September 2009, Edinburgh
Data Integration
• The data integration can be described on three levels of
complexity:
– the first layer is the integration of information from
heterogeneous resources by collecting data between different
database to allow an unified query schema;
– the second layer consists in the identification of correlative
associations across different datasets, generally using ontology
support, to provide a comprehensive and coherent view of the
same objects in light of different data sources;
– the third layer is mapping information gained about interacting
objects into networks and pathways that may be used as basic
models for the underlying cellular systems.
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway Tools framework
• The SysBio-Gateway tools framework are implemented for
the following main purpose:
– Simulation of Ordinary Differential Equation to solve the
mathematical models based on Xppaut program.
– In silico parameter values estimation to develop new cellular
system biology models.
– Visualization of the Protein structure and the correlated Connolly
surfaces.
– Analysis of protein-protein interactions network (search for the
first neighbourhood, search for shortest path and common
annotations)
– Modelling the protein mutant starting from Single Nucleotide
Polymorphism data based on Modeller program.
– Image processing oriented to support tissue microarray analysis.
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway Tools framework
• The global optimization algorithm relies on an evolution
strategy for solving the uncertainty of parameters values:
– The system accepts as input a ODE based model (formatted as
plain text or encoded in the SBML standard) and the
experimental data and outputs the best fitting parameters.
– During the computation candidate solutions of separated
evolution processes are swapped every k iterations thanks to a
relational database.
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway Ontology
• The databases developed in the frame of SysBio-Gateway
are enriched by the ontological integration.
– The ontology used concern all levels of molecular biology, from
genes to proteins to pathways, tissues and diseases aspects.
– As example, we used Gene Ontology (GO) for genes annotation
and KEGG Pathway Ontology (derived from the hierarchical
organization of KEGG pathways) for biological networks.
– Ontology provides not only the availability of a commonly
accepted vocabulary, which facilitates data sharing and
information querying, but also increases the performance of
statistical and analytical studies.
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway Ontology
• Gene Ontology example
PARENT TERM
GO TERM
CHILDREN
TERMS
– Different genes and gene products are related to the ontology
terms through different evidences (i.e.: Inferred from Experiment,
Inferred from Sequence or Structural Similarity, Inferred from
Electronic Annotation)
– „is_a‟ is the relation that characterizes the link among parents
and children. Other important relations exist, such as „part_of‟
and „regulates‟.
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
• SysBio-Gateway is an example of unified framework
which embraces a set of specialized biomedical databases
and web resources oriented to different biological topics
such as:
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Biological processes (Cell Cycle)
Pathologies (Breast Cancer)
Organs (Brain and the Nervous System)
Protein families (Protein kinases)
Protein mutations (Protein C mutations)
Tissues (Tissue microarray)
• SysBio-Gateway relies both on a common methodology
of data integration and a set of tools which have been
developed ad hoc to enables the investigation in a systems
biology perspective
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
Cell Cycle Database
• The “Cell Cycle Database” (CCDB) is a resource which
collects useful information about genes and proteins
involved in the cell cycle process and mathematical models
of the cell cycle process.
• The integrating information belongs to the following
eukaryotic organisms:
– the budding yeast Saccaromyces cerevisiae
– the Homo sapiens
• Yeast and human organism have been chosen since a
deep knowledge of their cell cycle machinery is available
and an evolutionary conservation between the basic
regulatory events of the cell cycle has been demonstrated.
Luciano Milanesi 14-15 September 2009, Edinburgh
CCDB: the web interface
• Cell Cycle Database is accessible through a web interface
made up of HTML pages dynamically generated from PHP
scripts.
• URL:
http://www.itb.cnr.it/cellcycle/
Luciano Milanesi 14-15 September 2009, Edinburgh
CCDB: the integrative system
Resources provided as
external links
Resources from which data
are taken
Luciano Milanesi 14-15 September 2009, Edinburgh
CCDB Gene Report: main features
• Gene report collects
information integrating
data from different table;
• Gene report is linked to
different external
biological databases;
• Gene report is linked to
protein report.
Luciano Milanesi 14-15 September 2009, Edinburgh
CCDB Protein Report: main features
• Protein report collects
information integrating
data from different
tables
• Protein report is linked
to different biological
databases from which
we take data.
• Protein report is linked
to gene report
Luciano Milanesi 14-15 September 2009, Edinburgh
CCDB Model Report
• users can find:
– the mathematical
description of each
model
– the kinetic and
differential equations
– the related parameters
(the rate constants and
the initial protein
concentrations) defined
for the simulation
analysis.
Luciano Milanesi 14-15 September 2009, Edinburgh
Mathematical section
Luciano Milanesi 14-15 September 2009, Edinburgh
Simulation section
User can perfom the simulation of a
single ODE system describing a cell
cycle model
2D plot: image exported in png using GnuPlot
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
G2BCDB web interface
http://www.itb.cnr.it/breastcancer.
Luciano Milanesi 14-15 September 2009, Edinburgh
Genes-to-System Breast Cancer Database
• The Genes-to-Systems Breast Cancer (G2SBC)
Database is a bioinformatics resource to integrate the
information about genes, transcripts and proteins which
have been reported in literature to be altered in breast
cancer cells.
• The resource includes a section dedicated to mathematical
models related to carcinogenesis, tumor growth and tumor
response to treatments.
• This comprehensive resource is dedicated to molecular and
systems biology of breast cancer, including both the
building-blocks level (genes, transcripts and proteins) and
the systems level (molecular and cellular systems).
Luciano Milanesi 14-15 September 2009, Edinburgh
Genes-to-System Breast Cancer Database
Luciano Milanesi 14-15 September 2009, Edinburgh
G2BCDB: web interface and analysis tools
• Query system at molecular, systems and cellular level
• Ontology based query system
• Query system based on biochemical pathways and proteinprotein interaction network
• Common annotations (in a gene set) search tool
• Mathematical models analysis and simulation (with a
specific connection with the breast cancer genes with the
Cell Cycle Database and the cell cycle related models)
Luciano Milanesi 14-15 September 2009, Edinburgh
G2BCDB: test case
Example of analysis combining the use of G2SBC Database tools
a)
b)
c)
Query based on the
clustering coefficient of
breast cancer genes in the
PPIs network
The breast cancer gene
INHBC
has
a
high
clustering
coefficient,
equal
to
0.8,
and
establishes 6 interactions
(Gene Degree)
INHBC along with the
genes
in
its
first
neighbourhood in the PPIs
network are submitted to
the tool which shows the
common annotations
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
Nervous System Database
• The Nervous System Database (NSD) deals with the data
integration of the Nervous System regarding:
– Knowledge about biological components, such as genes and
proteins, are collected together with information at the system
level, such as protein networks and molecular pathways, that are
relevant for a better exploration of neural systems
– The annotations stored in NSD are associated to ontological
terms: this solution provides a semantic layer to improve data
storage, accessibility and sharing and represents an instrument
to identify relations among biological components
– The NSD systems supplies information about gene functions,
processes where they are involved and their spatial localization.
Luciano Milanesi 14-15 September 2009, Edinburgh
NSD: the web interface
http://www.itb.cnr.it/gncdb
Luciano Milanesi 14-15 September 2009, Edinburgh
Nervous System Database
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
Kinweb kinase database
• Eukaryotic protein kinase (ePKs) constitute one of the largest
recognized protein families represented in the human genome
• The common name kinase is applied to enzymes that catalyze the
transfer of the terminal phosphate group from ATP to a receptor
substrate.
• All kinase catalyze essentially the same phosphoryl transfer reaction,
however, they display remarkable diversity in their structures, substrate
specificity, and the pathways in which they participate.
• ePKs are important players in virtually every signaling pathway involved
in normal development and disease.
• The results of the human kinome analysis are collected in the KinWeb
database, available for browsing and searching over the internet,
where all results from the comparative analysis and the gene structure
annotation are made available, alongside the domain information.
Luciano Milanesi 14-15 September 2009, Edinburgh
Kinweb: the web interface
http://www.itb.cnr.it/kinweb
Luciano Milanesi 14-15 September 2009, Edinburgh
Kinweb kinase database
Luciano Milanesi 14-15 September 2009, Edinburgh
Kinweb: Kinase Protein Analysis
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
ProCMD: a 3D web resource for protein C mutants
• Activated Protein C (ProC) is an anticoagulant plasma
serine protease which also plays an important role in
controlling inflammation and cell proliferation
• Structure prediction and computational analysis of the
mutants have proven to be a valuable aid in understanding
the molecular aspects of clinical thrombophilia
• ProCMD is a relational database which collects data on
clinical, structural and functional properties of the protein C
variants with a graphic interface to search and visualize the
mutated residue in the protein structure
• The main purpose of this tools is to provide an easy access
to mutant structural data through the use of 3D interactive
viewers (VRML and RasMol)
Luciano Milanesi 14-15 September 2009, Edinburgh
ProCMD: the web interface
http://www.itb.cnr.it/procmd
Luciano Milanesi 14-15 September 2009, Edinburgh
ProcMD: test case
• The ProcMD system allows the user to retrieve entries
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by position in sequence of a mutated residue,
by aminoacid substitution,
by keyword amd by domain localization.
The results appears in a mutations list linked with a dedicated
„details page‟ where the mutant is fully described.
Luciano Milanesi 14-15 September 2009, Edinburgh
ProcMD: test case
• Details page for mutant G216D with 3D images gallery
Luciano Milanesi 14-15 September 2009, Edinburgh
SysBio-Gateway
www.itb.cnr.it/sysbio-gateway
Luciano Milanesi 14-15 September 2009, Edinburgh
Tissue Microarray -TMA Rep
• Tissue MicroArray technique is becoming increasingly important in
pathology for the validation of experimental data from transcriptomics
analysis.
• We propose a Tissue MicroArray web oriented system that supports
researchers in managing bio-samples and that, through the use of
ontologies, enables tissue sharing in order to promote TMA
experiments design and results evaluation.
• Our system provides ontological description both for describing preanalysis tissue images and for identifying post-process image results,
which represents a crucial feature for promoting information exchange
• Through this system, users associate an ontology-based description
to each image uploaded into the database and also integrate
results with the ontological descriptions of genes identified in
each tissue.
Luciano Milanesi 14-15 September 2009, Edinburgh
TMA Platform Overview
Luciano Milanesi 14-15 September 2009, Edinburgh
Conclusion
• Here we present an integrated solution to explore part of
the information gained in the field of life science oriented to
systems biology.
• SysBio-Gateway integrated portal combines:
– bioinformatics approach, i.e. data integration using data
warehouse approach
– application of tools for the data analysis
– study of structural modifications - both for genome and proteins
– systems biology approach, that is the study of protein-protein
interaction networks
– molecular mathematical models
– pathological states under a systemic point of view.
Luciano Milanesi 14-15 September 2009, Edinburgh
Acknowledgments
• This work has been supported by:
– EGEE-III, BBMRI, EDGE European projects
– MIUR FIRB LITBIO, ITALBIONET, CNR-BIOINFORMATICS
• People of the Institute for Biomedical Technologies-CNR,
Milan involved in this work:
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Luciano Milanesi,
Roberta Alfieri,
Ettore Mosca,
Federica Viti,
Pasqualina D'Ursi,
Ivan Merelli
Chiara Bishop and John Hatton (Graphical Web Interface)
Luciano Milanesi 14-15 September 2009, Edinburgh