Life Science Integrated Demo

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Transcript Life Science Integrated Demo

SVM Classification of Multiple
Tumor Types
78.25% accuracy
DNA Microarray Data
Actual\Predicted BR PR LU CO LY BL ML UT LE RE PA OV MS BR
BREAST-BR
1
1
PROSTATE-PR
LUNG-LU
1
1
COLON-CO
3
LYMPHOMA-LY
6
BLADDER-BL
1
2
MELANOMA-ML
1
1
UTERUS-UT
2
LEUKEMIA-LE
1
5
RENAL-RE
PANCREAS-PA
OVARY-OV
Oracle
Data Mining
We feed multiple cancer types
data into the Oracle DB:
16,063 genes, 144 cancer
patients.
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2
1
MESOTHELIOMAMS
BRAIN-BR
Green=Correct
We mine the data
using Support Vector
Machines and create
the confusion matrix
Multiple Examples of tumor tissue (public data from Whitehead/MIT)
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3
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Red=Errors
SVM Classification of Multiple
Tumor Types
78.25% accuracy
Actual\Predicted
BR
BREAST-BR
1
PR
LU
CO
LY
BL
ML
1
3
LYMPHOMA-LY
6
1
1
UTERUS-UT
1
MS
BR
1
5
RENAL-RE
MESOTHELIOMAMS
BRAIN-BR
OV
2
LEUKEMIA-LE
OVARY-OV
PA
2
MELANOMA-ML
PANCREAS-PA
RE
Oracle
Data 1Mining’s SVM models
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are able to accurately predict the
multi-class tumor problem with
78.25% accuracy.
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COLON-CO
BLADDER-BL
LE
1
PROSTATE-PR
LUNG-LU
UT
3
1
2
1
2
3
Green=Correct
Red=Errors
4
Identify Biomarkers for DLBC
Lymphoma Treatment Outcome
Attribute Importance
identifies genes correlated
with Lymphoma cancer.
Find a Cure for Lymphoma
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Literature search on Lymphoma
Set up a project workspace
Set up a meeting
Check lab protocols
Store cell histology images
Analyze gene expression results
Study the markers
Find a lead
Study the Markers
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Statistical analysis
Protein sequence analysis (Swissprot)
BLAST Search
Protein secondary structure study
Search of genes and genetic disorders (OMIM)
Pathway modeling
Data Analysis with JDeveloper
Data Analysis with JDeveloper
PKC Distribution Difference
Statistical Analysis
Create an External
Table to read data
from lymphoma.txt.
Statistical Analysis
Calculate Mean and
Standard Deviation
The t-test shows
that the PKC
expression levels in
cured and fatal
patients are
significantly
different.
Protein sequence analysis
Load SwissProt into Oracle XML DB
Load SwissProt into XML
DB to learn more about
expressed genes of interest
Load SwissProt into XML DB
FTP SwissProt data
and schema into
Oracle XML DB
Load SwissProt into XML DB
Access XML schema using
XML Spy (XML editor)
which connects to the
database using WebDAV
Load SwissProt into XML DB
Register the XML Schema
Once schema is registered,
XML DB automatically
generates tables
Describe the Table Generated