With the rapid development of high-throughput sequencing technologies, it becomes more easily for us to obtain various omics data including genome, transcriptome, and proteome through wet lab. These changes have brought a great benefits to life science community for understanding the molecular mechanism of cancer. However, there is lack of efficient data mining approaches to catch up the accumulation of omics datasets. To this end, it is urgent to develop computational systems biology methods and tools to identify pathogenic mechanisms of cancer through omics data integration, which will be helpful for prevention, diagnosis, treatment, and drug development of cancer. One way is to use computational approaches for drug repurposing. A number of computational methods have been used individually or in combination to systematically analyze different types of large-scale data to obtain meaningful interpretation for repurposing hypotheses. Another way is to evaluate associations between cancers and molecular features by analyzing individual omics data from multiple labs. e.g. Pathway biomarkers associated to clinically molecular subtypes and prognosis of cancers could be discovered and validated by analyzing data of multiple microarray platforms. In summary, one of the remaining challenges for understanding cancer is to mine novel characteristics through fusing multi-level omics data using computational system biology approaches.
Therefore, we conduct a Workshop on BIBM 2020 with the topic 'Integrating Omics Data for Cancer Therapies'.
The subtopics include, but are not limited to:
• Drug development of cancer through integrating omics data.
• Novel understanding of drugs for cancer.
• Machine learning methods for integrating multi-level omics data.
• Models for integrating multi-level omics data.
• Methods and tools for identifying risk pathways.
• Bioinformatics tools and databases for analyzing omics data.
• Pipeline for analyzing sequencing data.
• Novel findings on molecular biomarkers and signatures of cancer.
• Identification of novel causal phenotypes of cancer.
• Novel understanding of risk factors of cancer based on meta-analysis.
• Pan-cancer analysis through integrating multi-level omics data.
• Identification of molecular biomarker for human cancer.
All accepted papers will be published in IEEE Xplore Digital Library (EI index). Extension version of accepted papers will be published in Current Gene Therapy, Current Pharmaceutical Design, Integrative Cancer Therapies, and Current Bioinformatics following the journal's publication policy. All accepted papers will have to be presented by one of the authors at the Workshop.
Organizers:
Liang Cheng
Chief Editor of Current Gene Therapy
Professor and PI of Harbin Medical University
Email: liangcheng@hrbmu.edu.cn
Mingxiang Teng
Assistant Member of Moffitt Cancer Center
Email: mingxiang.teng@moffitt.org
Submission:
• We call for original and unpublished research contributions to the Workshop
• Please submit a full length paper (up to 6 page IEEE 2-column format) through the online submission system (you can download the format instruction
here. Electronic submissions in PDF format are required.
• Online submission system is
here.
• All accepted papers will be published in IEEE Xplore Digital Library (EI index).
Extension version of accepted papers will be published in
Current Gene Therapy, Current Pharmaceutical Design, Integrative Cancer Therapies, and Current Bioinformatics
following the journal's publication policy. All accepted papers will have to be presented by one of the authors at the Workshop.
Important date is as following:
| Submission deadline | Sep 30, 2020 |
| Acceptance notification | Oct 30, 2020 |
| Paper camera ready | Nov 18, 2020 |