Complexity

Biomolecular Networks for Complex Diseases


Publishing date
18 Aug 2017
Status
Published
Submission deadline
31 Mar 2017

1University of Saskatchewan, Saskatoon, Canada

2Central South University, Changsha, China

3Ulster University, Belfast, UK


Biomolecular Networks for Complex Diseases

Description

It is widely acknowledged that complex diseases or disorders (e.g., cancer, AIDS, and obesity) stem from the biomolecular dysfunction of not only their isolated components (e.g., genes, proteins, and metabolites). Biomolecular networks typically include gene regulatory networks, protein-protein interaction networks, metabolic networks, and signal transduction networks. With advances in high throughput measurement techniques such as microarray, RNA-seq, ChIP-chip, yeast two hybrid analysis, and mass spectrometry, large-scale biological data have been and will continuously be produced. Such data contain insightful information for understanding the mechanism of molecular biological systems and have proved useful in diagnosis, treatment, and drug design for complex diseases or disorders.

For this special issue, we strongly encourage authors to submit their original studies in modeling/construction, analysis, synthesis, and control of disease-related biomolecular networks.

Potential topics include but are not limited to the following:

  • Biomolecular network modeling and analysis
  • Prediction of disease molecules from biomolecular networks
  • Controllability and observability of biomolecular networks
  • Drug target identification from biomolecular networks
  • Biomolecular network based drug repositioning
  • Dynamic analysis of biomolecular networks
  • Parameter estimation of nonlinear dynamic molecular systems
  • Specific disease-related molecular networks
  • Disease-related protein complex or functional module detection
  • Application tools for biomolecular network visualization and analysis
Complexity
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Acceptance rate11%
Submission to final decision120 days
Acceptance to publication21 days
CiteScore4.400
Journal Citation Indicator0.720
Impact Factor2.3
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