Introduction to Computational Omics Lab
Computaional Omics Lab is composed of members majoring in Computer Science, Electronic Engineering, Automatic Control, and Life Sciences. Our research interests include integrative analysis of multiple omics data of diseases, developing algorithms, models and tools for integrative analysis, data mining from multiple omics data to identify genes, small RNAs and long noncoding RNAs that play critical roles in diseases, and establishing the association of microbiome with diseases. We welcome anyone who is interested in our researches.
Breast Cancer Integrative Platform(BCIP)
Breast cancer is a malignant tumor that develops from breast tissue. Worldwide, breast cancer is the leading type of cancer in women, accounting for 25% of all cases. The incidence rate has been steadily increasing since the 1970s.
Identification of genes that play critical roles in breast cancer is very important in deciphering the tumorigenesis of breast cancer and will contribute much to its treatment. Tha aim of BCIP is to help researchers to identify genes that may exert functions in development of breast cancer with published datasets. The BCIP platform integrates multiple omics data including transcriptome, copy number variation, microRNAs, pathway and gene functional networks. All the datasets are downloaded from EMBL-EBI, TCGA, and GEO of NCBI. Taking tumor heterogenity into consideration, we provide options for researchers to divide breast cancer samples into subgroups according to multiple histopathological features and clinical information such as PAM50 subtypes, stage, grade, lymph node status, survival, menopause status...+ details