This is the presentation of InSyBio in the 10th Conference of the Hellenic Society for Computational Biology and Bioinformatics - HSCBB15 which was held in Athens on October 2015. It presents our tool InSyBio BioNets and its case study on the discovery of diagnostic biomarkers for Parkinson Disease.

1. InSyBio BioNets: Utmost efficiency in
gene expression data and biological
networks analysis
Konstantinos Theofilatos
Christos Dimitrakopoulos
Christos Alexakos
Aigli Korfiati
Spiros Likothanassis
Seferina Mavroudi
InSyBio Ltd (www.insybio.com)
October
2015
10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
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2. Table of Contents
1. Introduction
2. Objectives
3. InSyBio BioNets approach
4. Parkinson Disease Biomarkers case study:
– Current knowledge about early stage Parkinson biomarkers
– Datasets and methods
– Experimental results
5. InSyBio BioNets user interface
6. InSyBio BioNets Availability
7. Discussion and conclusions
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

3. 1. Introduction
• Transcriptomics data are growing fast.
• Requirements are growing faster.
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• Existing analysis methods:
• Differential expression
analysis
• Systems biology
approaches
10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

4. 1. Introduction
• Systems medicine approach
Biomarkers from systems biology analysis.
Emphasis on the disease mechanisms and their
causes.
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

5. 2. Objectives
• Network-based biomarkers.
• Holistic biomarker approach.
• Integrated, user friendly web tool.
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

6. 3. InSyBio BioNets algorithmic flowchart for
trancriptomics analysis (part 1)
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

7. 3. InSyBio BioNets algorithmic flowchart for
trancriptomics analysis (part 2)
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

8. 4. Parkinson case study: Current knowledge about early
stage Parkinson biomarkers
• Diagnosis based on clinically detectable symptoms
(Chikina et al, 2015).
• Genetic and environmental causes (Aridon et al,
2011).
• Limited early stage diagnostic tests.
• New trend  genetic biomarkers from blood
samples (Scherzer et al, 2007), (Margis et al, 2011),
(Molochnikov et al, 2012) and (Chikina et al, 2015).
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

9. 4. Parkinson case study: Datasets and methods
• GDS2519 dataset from Gene Expression Omnibus
repository:
– 50 early stage PD patients, 22 control healthy subjects and 33
neurodegenerative disease control subjects.
• Algorthmic Framework:
– Normalization.
– Wilcoxon Rank Sum Differential Expression Analysis.
– Gene Co-expression networks construction and validation.
– Network based biomarkers prediction.
– Final integrative biomarkers extraction.
– SVM-based classifier training for validation of extracted biomarkers
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

10. 4. Gene Co-expression Networks Validation
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• Control Gene
Co-Expression
Network
• Parkinson Disease
Gene Co-Expression
Network
10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

11. 4. Parkinson case study: Experimental results
Method #PD Biomarkers Percentage of PD
related genes in
DisGeneNet (Piñero
et al, 2015)
Accuracy of an SVM
classifier using
leave one out cross
validation
approach
Wilcoxon Rank Sum
Method (Scherzer
et al, 2007)
834 7,47% ~96%
InSyBio BioNets
Approach
52 13,46% 100%
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 Less biomarkers
More accurate biomarkers
 Higher quality
10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

12. 4. Five most significant biomarkers
Gene
Symbol
Gene Name Confidence
Score
Molecular
Functionalities of
corresponding protein
Diseases Related with
this gene so far
HNRNPA3 Heterogeneous
nuclear
ribonucleoprotein A3
0.713 Nucleotide binding; nucleic acid
binding; RNA binding; poly(A) RNA
binding
Schizophrenia; Multiple Endocrine
Neoplasia Type 2a
DDX21 DEAD (Asp-Glu-Ala-
Asp) box helicase 21
0.704 nucleic acid binding; DNA binding;
RNA binding; double-stranded RNA
binding
Colorectal Carcinoma; Connective
Tissue Diseases; Gastric Antral
Vascular Ectasia
CACNG5 calcium channel,
voltage-dependent,
gamma subunit 5
0.677 voltage-gated calcium channel
activity; protein binding; ion
transmembrane transporter activity
Mental Disorders; Schizophrenia;
Bipolar Disorder
DNTT DNA
nucleotidylexotransf
erase
0.658 DNA binding; catalytic activity;
DNA-directed DNA polymerase
activity; DNA
nucleotidylexotransferase activity;
nucleotidyltransferase activity
Schizophrenia; Attention Deficit
Disorder with Hyperactivity;
Autistic Disorder; Diabetes
Mellitus, Type 1; Bipolar Disorder;
Multiple Sclerosis and so on
PRPF4B pre-mRNA
processing factor 4B
0.611 protein kinase activity; protein
serine/threonine kinase activity;
protein tyrosine kinase activity;
protein binding; ATP binding
NEOPLASM MALIGNANT;
Carcinoma; Parkinson Disease;
Familial paroxysmal dystonia
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

13. 5. InSyBio BioNets user interface
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

14. 5. InSyBio BioNets user interface
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

15. 5. InSyBio BioNets user interface
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

16. 5. InSyBio BioNets user interface
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

17. 5. InSyBio BioNets user interface
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

18. 6. InSyBio BioNets Availability
• Demo version: http://demo.insybio.com
• Beta version: http://beta.insybio.com
• Free Evaluation Version: Available upon request on
info@insybio.com
• Commercial Version: Available upon request on
sales@insybio.com
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

19. 7. Conclusions and future work
• InSyBio BioNets Key Properties
– Biomarker discovery using a novel systems medicine approach based on biological
network comparison which leads to more compact biomarker sets with increased
predictive accuracy;
– Semi-automated web based analysis of gene expression data and biological network
analysis;
– No need for personal supercomputers to perform difficult computing tasks: they are
now executed in our cloud infrastructure with minimum burden on the user’s pc.;
– Flexible analysis: Experienced users can select through a variety of provided
algorithms and parameters while inexperienced ones can use our fine-tuned default
setups;
– Informative Biomarkers Reports which integrate information from multiple sources
(OMIM, GeneCards and so on).
• Future work:
– InSyBio BioNets tool enhancement.
– PD biomarkers validation.
– Study on more neurodegenerative diseases.
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

20. Acknowledgements
• InSyBio participates in the NBG
Business Seeds Program
(https://www.nbg.gr/en/nbgseeds)
by National Bank of Greece
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

21. References
• Aridon, P., Geraci, F., Turturici, G., D'Amelio, M., Savettieri, G., & Sconzo, G. (2011).
Protective role of heat shock proteins in Parkinson's disease.Neurodegenerative
diseases, 8(4), 155.
• Chikina, M. D., Gerald, C. P., Li, X., Ge, Y., Pincas, H., Nair, V. D., ... & Sealfon, S. C.
(2015). Low‐Variance RNAs Identify Parkinson's Disease Molecular Signature in
Blood. Movement Disorders.
• Margis, R., Margis, R., & Rieder, C. R. (2011). Identification of blood microRNAs
associated to Parkinsońs disease. Journal of biotechnology,152(3), 96-101.
• Molochnikov, L., Rabey, J. M., Dobronevsky, E., Bonucelli, U., Ceravolo, R., Frosini, D.,
... & Mandel, S. A. (2012). A molecular signature in blood identifies early Parkinson’s
disease. Mol Neurodegener, 7(1).
• Piñero, J., Queralt-Rosinach, N., Bravo, A., Deu-Pons, J., Bauer-Mehren, A., Baron, M.,
Sanz, F., Furlong, L. (2015). DisGeNET: a discovery platform for the dynamical
exploration of human diseases and their genes. Database 2015: article ID bav028;
doi:10.1093/database/bav028.
• Scherzer, C. R., Eklund, A. C., Morse, L. J., Liao, Z., Locascio, J. J., Fefer, D., ... &
Gullans, S. R. (2007). Molecular markers of early Parkinson's disease based on gene
expression in blood. Proceedings of the National Academy of Sciences, 104(3), 955-
960.
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

22. Contact details
• Address:
– United Kingdom: InSyBio Ltd (www.insybio.com), Reg. No
8715590, 2nd floor, 109 Uxbridge Road, London, W5 5TL ,
Phone: +44 020 8567 3451
– Greece: InSyBio Private Company (www.insybio.gr), Kolchidos 48,
26332, Patra, Phone: +306973641685
• Email: info@insybio.com
• Skype: insybio
• Skype for businesses: insybio@insybio.onmicrosoft.com
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10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015

23. 23
THANK YOU FOR YOUR
ATTENTION
ANY QUESTIONS?
10th Conference of the Hellenic Society for Computational
Biology and Bioinformatics - HSCBB15
October
2015