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Related Concept Videos

MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
MicroRNAs01:22

MicroRNAs

MicroRNA (miRNA) are short, regulatory RNA transcribed from introns—non-coding regions of a gene—or intergenic regions—stretches of DNA present between genes. Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA ends...

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Related Experiment Video

Updated: Jun 4, 2026

miRNA Expression Analyses in Prostate Cancer Clinical Tissues
11:29

miRNA Expression Analyses in Prostate Cancer Clinical Tissues

Published on: September 8, 2015

Predicting microRNA modulation in human prostate cancer using a simple String IDentifier (SID1.0).

Maria C Albertini1, Fabiola Olivieri, Raffaella Lazzarini

  • 1Dipartimento di Scienze Biomolecolari, Sezione di Biochimica e Biologia molecolare, Università degli Studi di Urbino "Carlo Bo", Urbino, Italy. maria.albertini@uniurb.it

Journal of Biomedical Informatics
|February 22, 2011
PubMed
Summary

A new computer program, SID1.0 (simple String IDentifier), efficiently identifies shared messenger RNA (mRNA) targets and deregulated microRNAs (miRNAs) in prostate cancer. This tool aids in discovering novel cancer-related genes and miRNAs.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • MicroRNAs (miRNAs) play crucial roles in gene regulation and are implicated in various cancers, including prostate cancer.
  • Identifying specific miRNA targets and pathways is essential for understanding cancer development and progression.
  • Existing computational tools may lack the efficiency or scope for comprehensive miRNA target and pathway analysis.

Purpose of the Study:

  • To develop and validate a novel computational program, SID1.0 (simple String IDentifier), for efficient identification of shared mRNA targets among multiple miRNAs.
  • To identify novel miRNAs modulated in specific cancer pathways, particularly in prostate cancer.
  • To facilitate the discovery of new genes and miRNAs associated with prostate carcinoma.

Main Methods:

  • Development of SID1.0, a computationally inexpensive Fortran program utilizing an exhaustive search strategy.
  • Integration of data from established miRNA databases (PicTar, DIANA-MicroT 3.0) for screening shared target genes and pathways.
  • Application of SID1.0 to known cancer-associated miRNAs (miR-125b, miR-148a, miR-141) to identify mRNA targets and KEGG pathways.
  • Validation of predicted novel miRNAs and genes through preliminary expression analysis in prostate cancer cell lines and normal cells.

Main Results:

  • SID1.0 successfully identified shared mRNA targets and pathways for known cancer-related miRNAs.
  • The program predicted novel genes involved in prostate carcinoma.
  • SID1.0 facilitated the identification of previously unrecognized deregulated miRNAs in prostate cancer (miR-141, miR-148a, miR-19a, miR-19b).
  • Preliminary expression analysis supported the predicted roles of identified miRNAs in prostate cancer.

Conclusions:

  • SID1.0 is a novel and efficient software tool for analyzing miRNA-target interactions and identifying deregulated miRNAs in cancer.
  • The program enhances the discovery of novel cancer-related genes and miRNAs by screening existing databases.
  • SID1.0 provides a valuable computational resource for cancer research, particularly in identifying biomarkers and therapeutic targets.