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  • 1
    Publication Date: 2020-01-01
    Description: Acute lymphoblastic leukemia (ALL) is one of the most common hematological malignancies in children. Recent studies suggest the involvement of multiple microRNAs in the tumorigenesis of various leukemias. However, until now, no comprehensive database exists for miRNAs and their cognate target genes involved specifically in ALL. Therefore, we developed ‘LeukmiR’ a dynamic database comprising in silico predicted microRNAs, and experimentally validated miRNAs along with the target genes they regulate in mouse and human. LeukmiR is a user-friendly platform with search strings for ALL-associated microRNAs, their sequences, description of target genes, their location on the chromosomes and the corresponding deregulated signaling pathways. For the user query, different search modules exist where either quick search can be carried out using any fuzzy term or by providing exact terms in specific modules. All entries for both human and mouse genomes can be retrieved through multiple options such as miRNA ID, their accession number, sequence, target genes, Ensemble-ID or Entrez-ID. User can also access miRNA: mRNA interaction networks in different signaling pathways, the genomic location of the targeted regions such as 3′UTR, 5′UTR and exons with their gene ontology and disease ontology information in both human and mouse systems. Herein, we also report 51 novel microRNAs which are not described earlier for ALL. Thus, LeukmiR database will be a valuable source of information for researchers to understand and investigate miRNAs and their targets with diagnostic and therapeutic potential in ALL. Database URL: http://tdb.ccmb.res.in/LeukmiR/
    Electronic ISSN: 1758-0463
    Topics: Biology
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  • 2
    Publication Date: 2014-01-15
    Description: Background Given the estimate that 30% of our genes are controlled by microRNAs, it is essential that we understand the precise relationship between microRNAs and their targets. OncomiRs are microRNAs (miRNAs) that have been frequently shown to be deregulated in cancer. However, although several oncomiRs have been identified and characterized, there is as yet no comprehensive compilation of this data which has rendered it underutilized by cancer biologists. There is therefore an unmet need in generating bioinformatic platforms to speed the identification of novel therapeutic targets. Description We describe here OncomiRdbB, a comprehensive database of oncomiRs mined from different existing databases for mouse and humans along with novel oncomiRs that we have validated in human breast cancer samples. The database also lists their respective predicted targets, identified using miRanda, along with their IDs, sequences, chromosome location and detailed description. This database facilitates querying by search strings including microRNA name, sequence, accession number, target genes and organisms. The microRNA networks and their hubs with respective targets at 3'UTR, 5'UTR and exons of different pathway genes were also deciphered using the 'R' algorithm. Conclusion OncomiRdbB is a comprehensive and integrated database of oncomiRs and their targets in breast cancer with multiple query options which will help enhance both understanding of the biology of breast cancer and the development of new and innovative microRNA based diagnostic tools and targets of therapeutic significance. OncomiRdbB is freely available for download through the URL link http://tdb.ccmb.res.in/OncomiRdbB/index.htm.
    Electronic ISSN: 1471-2105
    Topics: Biology , Computer Science
    Published by BioMed Central
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