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Human microRNA similarity in breast cancer
Author(s) -
Ying Jing,
Donghai Li
Publication year - 2021
Publication title -
bioscience reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 77
eISSN - 1573-4935
pISSN - 0144-8463
DOI - 10.1042/bsr20211123
Subject(s) - microrna , similarity (geometry) , breast cancer , computational biology , disease , gene , biology , construct (python library) , cancer , bioinformatics , genetic similarity , gene regulatory network , biological network , breast disease , genetics , identification (biology) , structural similarity
MicroRNAs (miRNAs) play important roles in a variety of human diseases, including breast cancer. A number of miRNAs are up- and down-regulated in breast cancer. However, little is known about miRNA similarity and similarity network in breast cancer. Here, a collection of 272 breast cancer-associated miRNA precursors (pre-miRNAs) were utilized to calculate similarities of sequences, target genes, pathways and functions and construct a combined similarity network. Well-characterized miRNAs and their similarity network were highlighted. Interestingly, miRNA sequence-dependent similarity networks were not identified in spite of sequence-target gene association. Similarity networks with minimum and maximum number of miRNAs originate from pathway and mature sequence, respectively. The breast cancer-associated miRNAs were divided into seven functional classes (classes I-VII) followed by disease enrichment analysis and novel miRNA-based disease similarities were found. The finding would provide insight into miRNA similarity, similarity network and disease heterogeneity in breast cancer.

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