Background
However, advanced technologies have been developed in the treatment of various cancers, but the mortality rate from cancer is still very high. Drug resistance is a major problem for patients with cancer, which causes the treatment process to fail. In addition to inhibiting drug resistance, targeted therapy is also very important in treatment.
Main body:
Nowadays, miRNAs have gained increasing interest as they play a major role in both drug resistance and targeted therapy. MicroRNA (miRNA) is an important part of non-coding RNA that regulates gene expression at a post-transcriptional level. The prevailing studies about miRNA expression have been expanded into a variety of neoplasms. MiR-424 targets genes involved in various cellular processes and can participate in proliferation, differentiation, apoptosis, invasion, angiogenesis, and drug resistance and sensitivity.
Conclusion
In this study, we focus on the role of miR-424s in many cancer types by displaying the potential target genes associated with each cancer, as well as briefly describing the clinical uses of miR-424s as a diagnostic and predictive tool in malignancies.
Surfing data mining techniques for representing data sources have specifically attracted much attention among researchers. Given the curse of dimensionality in representing text using the traditional Bag-of-words models, lower-dimensional representation of text has been an important line of research due to its impact on many prediction, and recommendation tasks.
This thesis studies two main different viewpoints in text representation using content and citation information and then, different existing approaches along with their advantages, limitations and drawbacks are reviewed. A novel hybrid distributed technique for text representation is proposed where the textual content of documents is projected into a vector representation using an artificial neural network .
To test the performance of the new proposed technique, the well known link-prediction problem is selected to serve as a benchmark. A comparison is performed with other common techniques by predicting the existence of citation links between tuple of papers in a large citation graph.
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