Download Life Sciences Platform

Bioinformatics
Analytical Pipelines
Biological/
Clinical
Experiments
Instruments
Data PreProcessing
Analytical
Algorithms
Interpretation
of Results
Perl
Life Science Discovery Phases:
Perl
New Paper
Perl
Oracle LifeScripts
Sciences
Platform
Algorithms
Algorithms
Scripts
Algorithms
Scripts
New Drug
• Exploratory/Prototype Analysis
Files
• Application Development
DB
• Production System
Files
Files
Files
Files
Files
Files
Files
New Treatment
Files
DB
New DB Entries
CATG
00101
DLBC
Follicular
BioOracle
DNA Microarray Analysis of Lymphoma
Integrated Demo eSeminar Feb. 13th 2003
Biopsies
Samples
Instruments
Filtering
and PreProcessing
SQL, XML,
Java
Feature
Selection
SQL
Molecular
Pattern
Recognition
Interpretation
of Results
Discoverer
Oracle Data
Mining
Oracle Data
Mining
Reports
Feature
Selection
Bayesian
Classifier
Java Servlets
Portals
Affymetrix
Micro-Array
Microarray
Lab
Dataset from Golub et al Science 286:531-537.
Prediction:
DLBC
Follicular
More Examples
•
 DNA microarray analysis for
cancer classification
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Gene expressions from Leukemia cells
Target: Leukemia morphologies & treatment outcome
 Early disease screening
proteomic analysis
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Mass. spec. “peaks” from patient blood samples
Target: cancer or normal status
 Drug activity analysis
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Molecular characteristics of new drug candidates
Target: binding affinities to targets
Caprion
 Oracle Environment
 Discover & develop innovative
products for the diagnosis & treatment
– Oracle database
of diseases
– Oracle9i Application Server
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Scalability for a multi-TB system
Integration of all components with
existing computing environment
Security & protection of data integrity
 Key Advantages of Oracle
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Easy access & management of
integrated information
Rapid deployment of new ad hoc
query
Scalability necessary to
accommodate growth
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
Oracle9i Developer Suite
Oracle9i AS Discoverer
Oracle Warehouse Builder
“The Oracle Data Warehouse is a
key component of our IT platform
for proteomics analysis. The
massive amount of information we
produce every day requires a
system with proven performance to
effectively capture our biological
data”.
Bernard Gagnon, IT Director
Myriad Proteomics
 Mapping human protein interactions at  Oracle Environment
a system scale using two-hybrid &
– Oracle9i database with
mass spec.
partitioning
–
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Online database system to automate
laboratory flows
Databases for intermediate results
for quality control and tracking
Data marts that are specific to

customer needs
 Key Advantages of Oracle
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Ease of maintenance
Partitioning keeps up with end-user
demands for fast query times
Meets scalability needs
–
–
Oracle Enterprise Manager
Plan to use XML DB and
External Tables in 2003
“One of the keys to the technological
success of this project is our use of
Oracle software. Every aspect of our
business touches Oracle technology;
it’s a key component of our work”.
Marcel Davidson, Head of DB
Architecture & Administration
Applied Biosystems
 Enterprise software for laboratory
automation and integration
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Life Science LIMS
SQL*LIMSTM Software
 Key Advantages
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Sample and container
management to support complex
sample fan-outs
Full audit trail support to help
meet regulatory compliance
Application specific interfaces to
meet customers’ needs
Integration with third party
software
Supported by world-wide
professional services group
 www.appliedbiosystems.com
 Oracle Features
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Scalable, highly available
Open standards for
messaging and program
integration
Powerful reporting tools
Web publishing supported
5. Collaborate Securely
 Oracle Collaboration Suite
- Integrated communications
– Single enterprise search
across all repositories
 Internal & external
–
Flexible access
 Web, desktop
 Wireless and telephone
5. Collaborate Securely
 Oracle 10gAS Portal
–
Build personalized portals
 Oracle Workflow
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Automate laboratory and business processes
 Oracle 10gAS Files
–
Enable content management and collaboration
 Revision control, check-in/check-out, access
control
 Virtual Private Database
–
Different users have unique access privileges
 Auditing
–
Create audit trail to facilitate FDA compliance
 Oracle 10gAS Web Services
–
Standard way to collaborate through the web
Taratec e-Compliance
TM
An iFS Application
TM
 Taratec e Compliance
–
–
Built specifically to supports
FDA 21 CFR Part 11 Compliance
Designed for Life Sciences Data
& File Management
Screen shot or
diagram
 Features
–
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Versioning, Advance Searching,
Check-in/Check-Out
Integrated storage of files from
any source
Universal access through Web
browser
Complete Audit Trail of File
Operations
“With Oracle as the foundation,
we were able to develop a
solution that can secure a vast
array of file-based data with
vault like security.”
Bill Gargano, President and
COO Taratec Development
Corporation
Taratec and Taratec’s logo are registered trademarks of Taratec Development Corporation
© 1999 Taratec Development Corporation
GenSys Software
 Products
– GenSys/ELN (Electronic Laboratory
Notebook)
–
GenSys/R&D (Research & Discovery
software integration platform)
 Key Advantages
–
Most dependable
and secure enterprise-wide
application
–
Easy for Researchers to Learn & Use 
Open – Integrates well with Scientist
desktop & back-end applications (i.e.
registration, LIMS, search &
document management
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Also supports legal, regulatory and
records management users
www.gensys.com
Oracle 9i Features:
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XML - Automatic creation of XML
views
Adobe PDF Support
Oracle’s Scalability and flexibility
is key to GenSys’ enterprise
solution
iFS and XML DB offer powerful
potential in future releases
Web Services - Life Sciences Data
Sources & Applications
Oracle Web Services
SOAP, WSDL, UDDI Together
–
I3C participation
Web Service
Consumer
2. Find
UDDI
Repository
3. Invoke
SOAP
 Communicate
Oracle’s support
for web services
industry standards
Servlet
1. Publish
Service
WSDL Document
Web Service Supplier
Oracle10g Unbreakable Security

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


Complete data protection
Manage user access
Detect data misuse with Auditing
Facilitate regulatory compliance (HIPPA, 21 CFR PART 11)
Proven against 15 independent evaluations
Security Evaluations
Oracle
Microsoft
IBM
US TCSEC, Level B1
1
-
-
US TCSEC, Level C2
1
1
-
UK ITSEC, Levels E3/F-C2
3
-
-
UK ITSEC, Levels E3/F-B1
3
-
-
ISO Common Criteria, EAL-4
4
-
-
Russian Criteria, Levels III, IV
2
-
-
US FIPS 140-1, Level 2
1
Failed
TOTAL
15
1
0
University of California
San Diego School of Medicine
 The Patient Centered Access to Secure
Systems Online (PCASSO)
–
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178,000 Medical Records
Provides trusted access to a patient’s health
information from healthcare providers over the
Internet
Oracle Label Security & Virtual Private Database
 The security is locked to the data and therefore
can’t be subverted.
 No application coding needed to implement
security.
San Diego
Supercomputing Center
“In the beginning, we considered using MySQL,
Oracle, and another database. But when we
evaluated our project needs over the next ten years
and realized that our database could grow to
terabytes, we decided we needed a scalable
database and one that was reliable. We didn’t want
to be forced to change databases in the middle of
the project. …. “We do not need a lot of DBAs to
maintain the database.”
Joshua Li, Senior Computational Scientist, University of California, San
Diego, Supercomputing Center
Systemwide, SDSC relies on only three DBAs to run
over 40 Oracle databases.
AMR Research
“Regulatory compliance has become a business risk. Big
fines can be levied and the FDA can shut down
manufacturing lines. The FDA wants to make sure
companies have electronic signatures and a full,
auditable track record. All the IT systems deployed have
to guarantee full accountability and change management.
Oracle offers full traceability of the database. In other
products, you have to make sure the application that’s
using the data gives you the change management. Oracle
provides security and authentication built into the
database technology.”
Roddy Martin, Service Director of Consumer Package Goods and Life
Sciences, AMR Research
European
Bioinformatics Institute
“Our mission is to build molecular biology
databases of importance and place them in the
public domain so they can be used by the
research community as easily as possible.”
Peter Stoehr, Head of Database Operations, EBI
“Researchers tap directly into the data
repository we host here. We’re an international
data repository.”
Weimin Zhu, Head of Database Application Group, EBI
Oracle’s Contribution to Life Sciences
Find me any compound that looks like my current
structure, and that has been tested on any assay in my
company where the IC50>200nM, where I know that I
have a unique patent position, and hasn't been published
in any journal?
Oracle9i
select c.id, p.structure,
from compound c, protein p, assay a
where a.compound_id = c.id
and a.protein_id = p.id
and a.company = “BIO_SYS”
and a.IC50 > 200nM
and similar_to(p.id, “protein kinase”)
and not_published(p.id, “Medline”)
and extract_value(value(p.id), ‘Dgene/Protein/Id’) = p.id
Message
XML
Text
Relational
Image
IDC Analysts
“Even IBM's own partners say that DB2
and DiscoveryLink have failed to gain
much ground in the life sciences despite
IBM's giveaways. According to Hall,
Oracle, the "de facto standard," still holds
a commanding 75 percent to 80 percent
market share in this vertical.”
Mark Hall, Director of Life Sciences, IDC, in InfoWeek 12/12/2002
Life Sciences Highlights
 Life Sciences featured in Oracle Magazine
–
Features San Diego Supercomputer Center,
European Bioinformatics Institute, and
Celera Genomics Group
 InfoWorld article
–
Even IBM's own partners say that DB2 and DiscoveryLink have
failed to gain much ground in the life sciences despite IBM's
giveaways. According to Hall, Oracle, the "de facto standard," still
holds a commanding 75 percent to 80 percent market share in
this vertical.
 Mark Hall, Director of Life Sciences, IDC, in InfoWeek 12/12/2002
 BioInform article, Feb 2003
–
Oracle currently claims to hold 85 percent of the life science
research database market, but the company isn't resting on its
laurels. On the contrary, the database giant is expanding the
capabilities of its software in a bid to retain its edge in the
increasingly competitive market.
Additional Life Sciences Information
 Server Technology Development,
Life Sciences Product Management Team
–
–
–
[email protected]
[email protected]
[email protected]
 OTN
–
http://otn.oracle.com/industries/life_sciences/content.html
 Oracle Life Sciences Platform
 Tech eSeminars, white papers, Partner Solutions, Customer
Profiles, OTN Discussion Forum, etc.
 Oracle.com
–
http://www.oracle.com/industries/life_sciences/index.html?content.html
 Internal site
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http://bioinformatics.us.oracle.com
Oracle Life Sciences
User Community
 Customer Advisory Board (CAB)
 User group meetings being formed in North
America, Europe, and Asia Pacific.
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May 2003 in Hinxton Hall Conference Centre, Wellcome Trust
Genome Campus, Hinxton, UK
Sept 10, 2003, OracleWorld, San Francisco
 Discussion Forum on OTN
 “Oracle Life Sciences” SourceForge.net project
administered by SDSC to facilitate code &
experience sharing:
http://sourceforge.net/projects/oraclelifesci/
Oracle10g
“The Bioinformatics Release”
Life Sciences 10g Features
 Data Access
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Heterogeneous transportable tablespaces
Merge enhancements
 Variety of Data Types
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XML DB enhancements
Enhanced text processing and searches (to cluster and classify)
Network Data Model feature for managing “graph” databases
 Scalability and High Throughput
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Grid
Distributed query optimization
Data pump
 Finding Patterns and Insights
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Data Mining: DM4J GUI, 2 New Algorithms (SVMs & NMF) , PL/SQL API
BLAST
Text Mining
Regular expression searches
Expanded basic statistics
IEEE floating point
 Collaborate Securely
Oracle Data Mining
BLAST
CATG
00101
 Implemented using a table function interface
 BLAST search functions can be placed in SQL
queries
 Different functions for match & alignment
 SQL queries can be used to pre-filter database of
sequences & post-process the search results
 Combination of SQL queries & BLAST is very
powerful and flexible
Oracle Data Mining
BLAST
 Web Services GUI (available via OTN)
CATG
00101
Sample BLAST Query
 For the query sequence “ATCGCGTT”,
find the top 3 matches above a similarity
threshold from each organism
select seq_id, organism, score, expect
from (select t.seq_id, t.score, t.expect, g.organism,
RANK() OVER (PARTITION BY organism
ORDER BY score DESC) as o_rank
from SwissProt_DB g,
Table(SYS_BLASTP_MATCH (‘ATCGCGTT’,
cursor (select seq_id, sequence from
SwissProt_DB), 5)) t /* expect_value */
where t.seq_id = g.seq_id) where o_rank <= 3
CATG
00101
seq_id, organism, score, expect
o_rank <= 3
RANK
seq_id, organism, score, expect
t.seq_id = g.seq_id
seq_id, score, expect
SwissProt_DB
 BLAST “Delighters”
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SYS_BLASTP_MATCH
Queries performed in the database
Ability to perform combinatorial
query_sequence, parameters
SwissProt_DB
queries e.g. sequence similarity
AND annotation contains “Lymphoma”
Oracle Data Mining
 New GUI: “DM4J”
–
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JDeveloper GUI add-in wizards
for building data mining
components in the database
Results browser
 New algorithms
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Support vector machines
 To handle very wide & shallow data
 Regression
–
Nonnegative Matrix Factorization
 Feature creation
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Ability to mine “text” data
 Combine unstructured data and
structured data
 Pl/SQL API
Oracle Text Enhanced
Advanced Text Searches
 Perform enhanced
information searches
(using Oracle data mining functionality)
 Ability to perform fast autoclustering of documents,
URLs etc. into natural
groupings for more useful
searches
 Ability to provide “example
documents” search and
classify documents “likely” to
be similar based on patterns
beyond simple key word
searches
New Statistics & SQL Analytics
 Ranking functions
 Descriptive Statistics
rank, dense_rank, cume_dist, percent_rank,
ntile
–
 Window Aggregate functions
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(moving and cumulative)
– Avg, sum, min, max, count, variance, stddev,
first_value, last_value
 LAG/LEAD functions
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Sum, avg, min, max, variance, stddev, count,
ratio_to_report
 Statistical Aggregates
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Correlation, linear regression family, covariance
 Linear regression
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 Correlations
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Direct inter-row reference using offsets
 Reporting Aggregate functions
Fitting of an ordinary-least-squares regression
line to a set of number pairs.
Frequently combined with the COVAR_POP,
COVAR_SAMP, and CORR functions.
average, standard deviation, variance, min, max, median
(via percentile_count), mode, group-by & roll-up
DBMS_STAT_FUNCS: summarizes numerical columns of
a table and returns count, min, max, range, mean,
stats_mode, variance, standard deviation, median,
quantile values, +/- 3 sigma values, top/bottom 5 values
Pearson’s correlation coefficients, Spearman's and
Kendall's (both nonparametric).
 Cross Tabs
–
Enhanced with % statistics: chi squared, phi coefficient,
Cramer's V, contingency coefficient, Cohen's kappa
 Hypothesis Testing
–
t-test , F-test, One-way ANOVA, Chi-square, Mann
Whitney, Kolmogorov-Smirnov, Wilcoxon signed ranks
 Distribution Fitting
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Normal, uniform, Poisson, exponential, Weibull
 Pareto Analysis (documented)
–
80:20 rule, cumulative results table
Other Features Important to Life
Sciences
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
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


Grid Computing
IEEE Floating Point
XML DB
Heterogeneous Transportable Tablespaces
Distributed Query Optimization
Network Data Model
Upsert” (Merge), or not
Regular Expression Searches
Grid Computing
 Automated job scheduling
across Grid
 Already has been lots of
support for Grid concepts
provided within Oracle
environment
–
–
–
–
Distributed queries
External tables
Security
RAC
 Participate in Global Grid
Forum
 Incremental Grid support
IEEE Floating Point
 Support for industry standard treatment of
numbers and precision
 Critical for compute intensive operations
 Faster performance
XML DB
 Already have best support for XML today
 Applications can use standard SQL/XML operators to
generate complex XML documents from SQL queries
and to store XML documents
 The XML Parser is also extended to support the updated
and new W3C XML standards
 Support for evolution of XML schemas
 Major improvements in XML processing performance
–
XML Developer Kit (XDK) libraries and interfaces in Java, C, and C++ all
transparently support the database XMLType, increasing throughput and
scalability without high resource and processing costs. Additionally, the
architectures been redesigned using a pipeline process model and SAX to
increase performance while reducing resources.
Heterogeneous Transportable
Tablespaces
• Mechanism to quickly move a tablespace
across Oracle databases
• Most efficient means to move bulk data
between databases.
• Enhance to support cross platforms and
operating systems
source
database
target
database
Distributed Query Optimization
 Excellent support for distributed
queries today
 Performance addressed in each
release
 Cost-based optimizer enhanced to
capture complete statistics for remote
tables
 Considers network bandwidth and
latency in deciding what parts of the
query plan should be remotely mapped
Flat files
MySQL
Network Data Model
 Model, store, manage and
analyze generic
connectivity relationships
in the DB,
–
–
i.e. represent data as nodes
and links
Can model hierarchies, logical
or spatial information,
directionality
 Network analysis at client
or application level, e.g.
shortest-path, tracing,
within-distance analysis,
minimum cost spanning
tree, nearest neighbor
–
Network management, e.g. add,
delete, modify, load
“Upsert” (Merge), or not
 Provides conditional “insert or update” processing
–
e.g. perform check sum on annotation or DNA sequence
 Used in periodic data loads where new data is
merged with existing data and the content of source
and/or destination are unknown so INSERT or
UPDATE cannot be used exclusively
Merge Statement Example
MERGE
INTO
USING
ON
WHEN
table
table/view/subquery
( condition )
MATCHED
SKIP
WHEN
NOT
THEN
WHEN
update clause
( condition )
MATCHED
THEN
insert clause
Regular Expression Searches
 Enable Regexp support in database through SQL and
PL/SQL
 Provide SQL and PL/SQL functions for Regexp
matching and string manipulations
 Follow POSIX style Regexp syntax
 Support standard Regexp operators including *, +, ?, |,
^, $, ., [ ], {m, n}, etc.
 Include common extensions such as case-insensitive
matching, sub-expression back-references, etc.
 Compatible with popular Regexp implementations like
GNU, Perl, Awk
Oracle10g Customer Quotes
"Oracle 10g's new BLAST feature will enable us to easily integrate multiple types
of genomic and proteomic data for complicated queries used in the mining of our
proprietary protein-protein interaction and cDNA sequence datasets."
- Jake Chen, Principal Bioinformatics Scientist, Myriad Proteomics
“Using InforSense discovery workflows built upon the world leading Oracle data
mining, text mining and R&D Database functionality, researchers and
organizations can now automate large scale and complex knowledge discovery
and management activities with performance and reliability.”
- Yike Guo, CEO InforSense
"Oracle 10g's Network Data Model feature is great for building a semantic work
infrastructure. Oracle 10g's graphical representation is an excellent tool for
planning our Y2H protein interaction data storage needs and for building a
signaling network from our Nature-AfCS Molecule Pages Database."
- Joshua Li, Sr. Computational Scientist, San Diego Supercomputer Center / UCSD
"Thanks to Oracle 10g's Regular Expressions (RE) query support, it's no longer
necessary to export data from the database, process it with a RE enabled tool
and then import the data back into the database. Now, RE processing can be
handled with a single query."
- Marcel Davidson, Head of Database Administration, Myriad Proteomics
Oracle10g Customer Quotes
"With Oracle 10g, sequence data that formerly needed to exported,
BLASTed, and reimported, can now be analyzed with a single SQL
statement."
- Marcel Davidson, Head of Database Administration, Myriad Proteomics
"Oracle 10g's implementation of REs enables the expression of
complex Query logic-particularly against text strings-which is
extremely useful in bioinformatics applications where queries are often
formulated against complex genetic or proteomic code patterns."
- Jake Chen, Principal Bioinformatics Scientist, Myriad Proteomics
"Beyond Genomics, Inc., as a leading systems biology company,
believes that Oracle 10g's network data model will significantly
advance the integration of metabolomic, proteomic, transcriptomic,
and clinical data sets and the applications that derive value from these
data."
– Eric Neumann, Vice President Strategic Informatics, Beyond Genomics, Inc.
Oracle Life Sciences
Platform Summary
 Life sciences not just a “wet lab” environment
– In silico drug discovery now a critical component
– Oracle, the “de facto standard”, enjoys an 80% market share - IDC
 Enables you to
–
–
–
–
–
Access data from multiple sources
Integrate a variety of data types
Manage vast quantities of data
Find patterns and insights
Collaborate securely with other
researches
 Oracle 10g is an ideal platform for life sciences
Q U E S T I O N S
A N S W E R S