Data Mining: the computing process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. It is an interdisciplinary subfield of computer science.The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Aside from the raw analysis step, it involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating.
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To date the anatomic extent of tumor (TNM-classification) has been by far the most important factors to predict the prognosis of cancer patients. However, this classification provides limited...
RNA sequencing unlocks the mysteries hidden in the transcriptome. Whether your goal is gene expression analysis, gene fusion analysis, SNP analysis or miRNA expression analysis, achieving hig...
High-throughput screening is widely useful in identifying genes and pathways that drive changes in cell behavior such as cell cycle regulation, metastasis, and drug resistance. Millipor...
In prior work, we have pursued how tumor reactive monoclonal antibody (mAb), together with activators of innate immune cells, like NK cells, can augment antibody dependent cell-mediated cytot...
Molecular analyses of cancer biology have tended to segregate between a focus on nucleic acids – DNA, RNA and their modifications – and a focus on proteins and protein function. P...