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Updated: Feb 24, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
A database of breast oncogenic specific siRNAs
Atul Tyagi1, Manoj Semwal2, Ashok Sharma3
1Biotechnology Division, CSIR-Central Institute of Medicinal and Aromatic Plants, P.O.-CIMAP, Near Kukrail Picnic Spot, Lucknow, 226 015, Uttar Pradesh, India. ks26atul@gmail.com.
Researchers created the Breast Oncogenic Specific siRNAs (BOSS) database, a valuable resource for identifying specific small interfering RNAs (siRNAs) to target genes in breast cancer research and drug development.
Area of Science:
- Biochemistry
- Bioinformatics
- Molecular Biology
Background:
- Breast cancer poses a significant global health challenge, necessitating targeted gene therapies.
- RNA interference (RNAi) offers a promising avenue for gene silencing in cancer treatment.
- Identifying specific oncogene targets is crucial for developing effective breast cancer drugs.
Purpose of the Study:
- To develop a comprehensive database of experimentally validated breast oncogenic siRNAs.
- To provide a centralized resource for researchers studying siRNA-mediated gene repression in breast cancer.
- To facilitate the discovery of novel therapeutic strategies for breast cancer.
Main Methods:
- Compilation of siRNA data from scientific literature and patents.
- Development of the Breast Oncogenic Specific siRNAs (BOSS) database.
- Integration of bioinformatics tools, including siRNAMAP and BOSS BLAST.
Main Results:
- The BOSS database contains 865 entries of validated breast oncogenic siRNAs.
- Each entry includes detailed information such as siRNA sequence, target gene, cell type, and inhibition efficacy.
- Linked tools aid in selecting optimal siRNAs and locating them within oncogenes.
Conclusions:
- The BOSS database serves as a vital resource for breast cancer research and therapeutic development.
- It supports the identification and design of specific siRNAs for targeting oncogenes.
- This resource can accelerate the advancement of RNAi-based breast cancer treatments.
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