With the rapid development of sequencing technologies, it makes more easily for us to reveal the variations and expression levels of molecules in genome, transcriptome, and proteome through wet lab. This advantage has brought a great helpful in life science community for exposing the risk factors of human diseases. In comparison with the biological findings from wet lab, more knowledge needs to be mined from huge amounts of sequencing data. To this end, bioinformatics methods have been introduced to help researchers to identify much more causal genes, biomarkers associated with clinically molecular subtype and prognosis, and so on. Whereas, most of these methods focus on analyzing individual omics data, which can only provide a partial understanding of human diseases. Thus at present, the major challenge is to mine novel causal genes and phenotypes of diseases based on fusing multi-level omics data using system biology approaches, which can then improve gene therapy.
Therefore, I (Liang Cheng) propose a Special Issue of Current Gene Therapy about the topic 'System Biology Methods and Tools for Gene Therapy'.
In 2018, I have conducted a Special Issue "Human Disease System Biology" (PMID: 30306867) for 'Current Gene Therapy'.
The subtopics include, but are not limited to:
• The designment and development of disease-related ontologies.
• Machine learning methods for integrating multi-level omics data.
• Statistical methods for integrating multi-level omics data.
• Tools and databases for analyzing multi-level omics data.
• Pipeline for analyzing sequencing data.
• Novel findings on molecular biomarkers and signatures of human diseases.
• Identification of novel causal phenotypes of human disease.
• Novel understanding of risk factors of diseases based on meta-analysis.
• Novel understanding of drugs for human disease.
Important date is as following:
| Manuscript Due Date | Apr 30, 2019 |
| Final Decision Date | Jun 15, 2019 |
Note:
Compulsory Word templates
The manuscript could be submitted to:
Liang Cheng, Assoicated Professor of Harbin Medical University.
Email: liangcheng@hrbmu.edu.cn