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Updated: Feb 6, 2026

Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Integrated analysis of dysregulated lncRNA expression in breast cancer cell identified by RNA-seq study
Rashmi Tripathi1, Apoorva Soni2, Pritish Kumar Varadwaj1
1Department of Bioinformatics, Indian Institute of Information Technology, Allahabad, U.P, India.
Abstract:
Among all the sequencing techniques, RNA sequencing (RNA-seq) has galloped with pace adopting the profiling of transcriptomic data in almost every biological analytics area like gene regulation study, development biology and clinical research. Recently the discovery of differentially expressed genes across different conditions has outshone the barrier of genetic & epigenetic regulations. The present work identified and analyzed differentially expressed novel long non-coding RNAs (lncRNAs) for breast cancer. A complex computational pipeline was adopted for the study which includes analysis of 18498 differentially expressed genes with 4114 up-regulated and 3475 down-regulated transcripts. The overexpression of lnc-MTAP (CDKN2B-AS1), lnc-PCP4 (DSCAM-S1), and lnc-FAM (H19) in breast cells suggests that these lncRNAs may have significant role to play in breast cancer. These results validated the relevance of the dysregulation pattern in cancer cells due to the presence of lncRNAs. The study further opens a new scope for experimental analysis to confirm the aberrant expression pattern of these lncRNAs which may act as potential bio-markers for the diagnosis and early detection of breast cancer.
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