Computational Omics Lab

 

Breast Cancer Integrative Database(BCID)


Breast cancer is a malignant tumor that develops from breast tissue and the incidence rates have been steadily increasing since the 1970s. Worldwide, breast cancer is the leading type of cancer in women, accounting for 25% of all cases.
Breast cancer is a heterogeneous disease with a high degree of diversity in histopathology, and correspondingly it can be divided into categories according to the grade/stage and the expression of proteins and genes of the tumor. The data of our database is derived from publicly published databases consist of the EMBL-EBI, TCGA, and GEO dataset of NCBI. The BCID database is characterized by multi-omics integrated analysis (transcriptome, copy number variation, microRNA, pathway and gene functional network analysis), and divides the breast cancer samples into several subgroups according to histopathological features and clinical information. As a result, we look forward to supplying an information platform for functional study of breast cancer genes and discovering some candidate genes, which can contribute to the precise diagnosis and treatment of breast cancer.

 

Link to BCID

 

 

 

MetaLogo: generator and aligner for multiple sequence logos


MetaLogo can draw sequence logos for sequences of different lengths or from different groups in one single plot and align multiple logos to highlight the sequence pattern dynamics across groups, thus allowing users to investigate functional motifs in a more delicate and dynamic perspective. We provide users a public MetaLogo web server (http://metalogo.omicsnet.org), a standalone Python package (https://github.com/labomics/MetaLogo), and also a built-in web server available for local deployment. Using MetaLogo, users can draw informative, customized, aesthetic, and publishable sequence logos without any programming experience.

Link to MetaLogo

 

 

 

Lungcancer Database


Link to Lungcancer Database