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MicroRNAs have close relationship with human diseases. Therefore, identifying disease related MicroRNAs plays an important role in disease diagnosis, prognosis and therapy. However, designing an effective computational method which can make good use of various biological resources and correctly predict the associations between MicroRNA and disease is still a big challenge. Previous researchers have...
MicroRNAs (miRNAs) are small non-coding RNAs which cause target genes degradation or translational inhibition. Constructing functional miRNAs regulatory module can be a significant step towards the discovery of their regulatory roles in various development programs. In this paper, we present a Correlated Correspondence Regulatory Module model which builds on modified Correlated Topic Model (CTM)....
In this paper, we present a critical review of the various research currently being undergoing in applications of data mining for healthcare management. The objective of this study is to explore new and emerging areas of data mining techniques used in healthcare management. The applications included in this paper are infection control surveillance, diagnosis and treatment of various diseases, healthcare...
Wireless Sensor Networks produce large amount of data during their lifetime operation. Sometimes this data is in unknown format and bulky. Hence data storage and appropriate mining technique become a critical issue for this domain. Recent innovation in data mining technique receives attention in extracting knowledge from WSNs data. In this paper, we have proposed a Multidimensional Association rule...
Purpose: The analysis of syndrome distribution and the association between syndrome-syndrome in chronic gastritis (CG) patients can provide references for research about Traditional Chinese Medicine (TCM) diagnosis and treatment of CG. Method: This paper applies the investigation method of clinical epidemiology, adopts probability statistics method and comes up with the concept of associated density...
This research paper uses association rules and classification techniques to extract undiscovered information of diabetes. Previous phase of this research included the preliminary results of some undiscovered decision factors and side effects of diabetes, by considering diabetes type 1 and type 2 patients' data set. Advanced and reliable data mining techniques are used throughout this research to the...
Data mining has emerged as one of the major research domain in the recent decades in order to extract implicit and useful knowledge. This knowledge can be comprehended by humans easily. Initially, this knowledge extraction was computed and evaluated manually using statistical techniques. Subsequently,semi-automated data mining techniques emerged because of the advancement in the technology. Such advancement...
Human immunodeficiency virus type 1 (HIV-1) integrase (IN), which aids the integration of viral DNA into the host chromosome, is an essential enzyme in the lifecycle of this virus and also an important target for the study of anti-HIV drugs. Recently synthesized 12-mer EBR28 which was identified through the yeast two-hybrid system and could strongly bind to IN is one of the most potential small peptide...
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