In this paper, we present miRTarVis+, a Web-based interactive visual analytics tool for miRNA target predictions and integrative analyses of multiple prediction results. Various microRNA (miRNA) target prediction algorithms have been developed to improve sequence-based miRNA target prediction by exploiting miRNA-mRNA expression profile data. There are also a few analytics tools to help researchers predict targets of miRNAs.
The DiseaseConnect (http://disease-connect.org) is a web server for analysis and visualization of a comprehensive knowledge on mechanism-based disease connectivity. The traditional disease classification system groups diseases with similar clinical symptoms and phenotypic traits. Thus, diseases with entirely different pathologies could be grouped together, leading to a similar treatment design. Such problems could be avoided if diseases were classified based on their molecular mechanisms.
Approximately 80% of Stage II colon cancer patients are cured by appropriate surgery. However, 20% relapse, and virtually all of these people will die due to metastatic disease. Adjuvant chemotherapy has little or no impact on relapse or survival in Stage II colon cancer, and can only add toxicity without benefit for 80% of the target population that has been cured by surgery.
With this study, we provide a comprehensive reference dataset of detailed miRNA expression profiles from seven typesof human peripheral blood cells(NK cells, B lymphocytes, cytotoxic T lymphocytes, T helper cells, monocytes, neutrophils and erythrocytes), serum, exosomes and whole blood. The peripheral blood cells from buffy coats were typed and sorted using FACS/MACS. The overall dataset was generated from 450 small RNA libraries using high-throughput sequencing.
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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