Journal of
Systemics, Cybernetics and Informatics
 



ISSN: 1690-4524 (Online)


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Honorary Editorial Advisory Board's Chair
William Lesso (1931-2015)

Editor-in-Chief
Nagib C. Callaos


Sponsored by
The International Institute of
Informatics and Systemics

www.iiis.org
 

Editorial Advisory Board

Editors

Journal's Reviewers
 

Description and Aims

Submission of Articles

Areas and Subareas

Information to Contributors

Editorial Peer Review Methodology

Integrating Reviewing Processes


Detection of Minimal Set of Trips Causing the Necessity to Use Extra Vehicle for Vehicle Scheduling Problem
Katerina Pastircáková, Jaromír Šulc
(pages: 1-4)

Key Factors in the Success of Self - Directed Learning of Military Personnel - Taking Smartphone as an Example
Yen-Hsi Lo, Yen-Fen Lo, Po-Yun Chiang, Jung Hsiao
(pages: 5-8)

Machine Learning Based IP Network Traffic Classification Using Feature Significance Analysis
Te-Shun Chou, John Pickard, Ciprian Popoviciu
(pages: 9-12)

The Information System for US Stock Market: Fundamental and Technical Analysis
Sergejs Hilkevics, Galina Hilkevica
(pages: 13-24)

The Impact of Environmental and Social Performance on the Market Value of Shares of Czech Joint-Stock Corporations
Alena Kocmanova, Marie Pavlakova Docekalova, Iveta Simberova
(pages: 25-31)

Play the Game! Analogue Gamification for Raising Information Security Awareness (Invited Paper)
Margit Scholl
(pages: 32-35)

Using Informatics and Technology Practices for Academic Performance Review
Kim Moorning
(pages: 36-41)

Multiple Research Perspectives as a Paradigm to Co-Create Meaningful Real-life Experiences
Jan Detand, Marina Emmanouil
(pages: 42-46)

A Methodology to Integrate Regulatory Expertise, Research and Education to Accelerate Biomedical Device Translation
Diana Easton
(pages: 47-52)

Active Learning through Smart Grid Model Site in Challenge Based Learning Course
Ellen A. Kalinga, Kwame S. Ibwe, Nerey H. Mvungi, Hannu Tenhunen
(pages: 53-64)

Non-Linear Static Analysis of Masonry Buildings under Seismic Actions
Maria Luisa Beconcini, Paolo Cioni, Pietro Croce, Paolo Formichi, Filippo Landi, Caterina Mochi
(pages: 65-70)

Toward an Engaging Hands-on Environment for a Beginning Networking and Security Class
Lopamudra Roychoudhuri
(pages: 71-76)

Designing Representations, Affecting Reality: A Meta-Model Proposal to Address the Question of Design Epistemology from the Perspective of Cognitive Science
Andrea Zammataro
(pages: 77-80)

Dielectrophoretic Movement of Cell around Surface Electrodes in Flow Channel
Yusuke Takahashi, Shigehiro Hashimoto, Manabu Watanabe
(pages: 81-87)


 

Abstracts

 


ABSTRACT


GEGEINTOOL: A Computer-Based Tool for Automated Analysis of Gene-Gene Interactions in Large Epidemiological Studies in Cardiovascular Genomics

Oscar Coltell, José M. Ordovás, Carmen Saiz, Manuel Forner, Francisco Gabriel, Dolores Corella


Current methods of data analysis of gene-gene interactions in complex diseases, after taking into account environmental factors using traditional approaches, are inefficient. High-throughput methods of analysis in large scale studies including thousands of subjects and hundreds of SNPs should be implemented. We developed an integrative computer tool, GEGEINTOOL (GEne- GEne INTeraction tOOL), for large-scale analysis of gene-gene interactions, in human studies of complex diseases including a large number of subjects, SNPs, as well as environmental factors. That resource uses standard statistical packages (SPSS, etc.) to build and fit the gene-gene interaction models by means of syntax scripts in predicting one or more continuous or dichotomic phenotypes. Codominant, dominant and recessive genetic interaction models including control for covariates are automatically created for each SNP in order to test the best model. From the standard outputs, GEGEINTOOL extracts a selected set of parameters (regression coefficients, p-values, adjusted means, etc.), and groups them in a single MS Excel Spreadsheet. The tool allows editing the set of filter parameters, filtering the selected results depending on p-values, as well as plotting the selected gene-gene interactions to check consistency. In conclusion, GEGEINTOOL is a useful and friendly tool for exploring and identifying gene-gene interactions in complex diseases.

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