NDLI: In Silico Identification of OncomiRs in Different Cancer Types

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In Silico Identification of OncomiRs in Different Cancer Types

Content Provider	Springer Nature Link
Author	Bandyopadhyay, Sanghamitra Bhattacharyya, Malay
Copyright Year	2012
Abstract	The diagnosis, prognosis and therapeutics of various kinds of cancers are challenging domains of research. Current landmark of cancer research at the molecular level mainly focuses on the regulation of genes for studying cancer pathways. Recent investigations highlight that there is a significant association of a class of short RNAs in the progression of different types of cancer. In this paper, the involvement of microRNAs (miRNAs), a type of small endogenous RNAs, is explored in two categories of cancers in human, one tumor-based and another non-tumorous. A new approach of in silico identification of the miRNAs that might be associated with these cancer types is proposed. The oncomiRs, miRNAs associated with cancer, are identified by analyzing the differentially co-expressed miRNAs and further exploring how they cooperate with each other. Extensive computational analysis on miRNA expression profiles for the discovery of novel oncomiRs is pursued. The results are found to be promising by going deep into the regulatory information available on oncogenes from the up-to-date literature. Some of the miRNAs as oncogenic are identified by the approach like hsa-miR-186 and hsa-miR-154 for leukemia and prostate cancer, respectively, which are not included in standard databases. However, some of the emerging studies give evidences to these findings. Statistical and biological studies, on the other hand, strengthen the effectiveness of the proposed method in futuristic investigations for the exploration of undiscovered oncomiRs. On the whole, these analyses provide insight into the discovery of miRNA markers.
Starting Page	15
Ending Page	23
Page Count	9
File Format	PDF
ISSN	22502106
Journal	Journal of The Institution of Engineers (India): Series B
Volume Number	93
Issue Number	1
e-ISSN	22502114
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-05-17
Publisher Place	India
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Network analysis microRNA Communications Engineering, Networks Differential expression Cancer
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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