Integrated Analysis of Multiscale Large-Scale Biological Data for Investigating Human Disease 2016

With the development of high-throughput omics technologies, more and more omics data are generated.It has become common to have multiomics data for the same samples which make the integrative analysis possible.But the data integration is still challenging since there are only a limited number of methods to do such analysis.To stimulate the methodology development and applications of multiomics analysis, we collected 14 novel studies of large scale multiomics data for biomedical researches.P. Y. De Silva and G. U. Ganegoda critically analyzed various methods used for encoding and encrypting data onto DNA and identified the advantages and capability of every scheme to overcome the drawbacks of previous methods.J. Wu et al. integrated the MGI, GEO, and miRNA database to analyze the genetic regulatory networks under morphology difference of integument of humans and mice.And they found that the gene expression network in the skin was highly divergent between human and mouse.L.-W.Liu L. et al. analyzed 303 samples of ovarian serous cystadenocarcinoma and the corresponding RNA-seq data.They established a risk assessment model of five genes and the AUROC value was 0.67 when predicting the survival time in testing set.S. Wang et al. proposed a new hybrid algorithm called HICATS that incorporated imperialist competition algorithm (ICA) which performs global search and tabu search