Book ChapterDOI
City Block Distance for Identification of Co-expressed MicroRNAs
Sushmita Paul,Pradipta Maji +1 more
- pp 387-396
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TLDR
The proposed method judiciously integrates the merits of robust rough-fuzzy c-means algorithm and normalized range-normalized city block distance to discover co-expressed miRNA clusters and helps to handle minute differences between two miRNA expression profiles.Abstract:
The microRNAs or miRNAs are short, endogenous RNAs having ability to regulate gene expression at the post-transcriptional level. Various studies have revealed that a large proportion of miRNAs are co-expressed. Expression profiling of miRNAs generates a huge volume of data. Complicated networks of miRNA-mRNA interaction increase the challenges of comprehending and interpreting the resulting mass of data. In this regard, this paper presents the application of city block distance in order to extract meaningful information from miRNA expression data. The proposed method judiciously integrates the merits of robust rough-fuzzy c-means algorithm and normalized range-normalized city block distance to discover co-expressed miRNA clusters. The city block distance is used to calculate the membership functions of fuzzy sets, and thereby helps to handle minute differences between two miRNA expression profiles. The effectiveness of the proposed approach, along with a comparison with other related methods, is demonstrated on several miRNA expression data sets using different cluster validity indices and gene ontology.read more
References
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Book
Fuzzy sets
TL;DR: A separation theorem for convex fuzzy sets is proved without requiring that the fuzzy sets be disjoint.
Book
Pattern Recognition with Fuzzy Objective Function Algorithms
TL;DR: Books, as a source that may involve the facts, opinion, literature, religion, and many others are the great friends to join with, becomes what you need to get.
Journal ArticleDOI
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
TL;DR: A new graphical display is proposed for partitioning techniques, where each cluster is represented by a so-called silhouette, which is based on the comparison of its tightness and separation, and provides an evaluation of clustering validity.
Journal ArticleDOI
MicroRNA expression profiles classify human cancers
Jun Lu,Gad Getz,Eric A. Miska,Eric A. Miska,Ezequiel Alvarez-Saavedra,Justin Lamb,David Peck,Alejandro Sweet-Cordero,Alejandro Sweet-Cordero,Benjamin L. Ebert,Benjamin L. Ebert,Raymond H. Mak,Raymond H. Mak,Adolfo A. Ferrando,James R. Downing,Tyler Jacks,H. Robert Horvitz,H. Robert Horvitz,Todd R. Golub,Todd R. Golub,Todd R. Golub +20 more
TL;DR: A new, bead-based flow cytometric miRNA expression profiling method is used to present a systematic expression analysis of 217 mammalian miRNAs from 334 samples, including multiple human cancers, and finds the miRNA profiles are surprisingly informative, reflecting the developmental lineage and differentiation state of the tumours.
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