ArticleRNA (New York, N.Y.)2013
Searching the coding region for microRNA targets.
Article in RNA (New York, N.Y.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 35 citations in OpenAlex.
- microT-CNN: an avant-garde deep convolutional neural network unravels functional miRNA targets beyond canonical sites.Briefings in bioinformatics · 2024Article
- In silico methods for predicting functional synonymous variants.Genome biology · 2023Review
- BoT-Net: a lightweight bag of tricks-based neural network for efficient LncRNA-miRNA interaction prediction.Interdisciplinary sciences, computational life sciences · 2022Article
- Synonymous ADAMTS13 variants impact molecular characteristics and contribute to variability in active protein abundance.Blood advances · 2022Article
- Synonymous Variants: Necessary Nuance in Our Understanding of Cancer Drivers and Treatment Outcomes.Journal of the National Cancer Institute · 2022Review
- Identification and Characterization of MicroRNAs Involving in Initial Sex Differentiation ofBiology · 2022Article
- Exogenous miRNA: A Perspective Role as Therapeutic in Rheumatoid Arthritis.Current rheumatology reports · 2021Review
- Prediction methods for microRNA targets in bilaterian animals: Toward a better understanding by biologists.Computational and structural biotechnology journal · 2021Review
- miRNA Targets: From Prediction Tools to Experimental Validation.Methods and protocols · 2020Review
- LncMirNet: Predicting LncRNA-miRNA Interaction Based on Deep Learning of Ribonucleic Acid Sequences.Molecules (Basel, Switzerland) · 2020Article
- Regulation of cell-type-specific transcriptomes by microRNA networks during human brain development.Nature neuroscience · 2018Article
- Review
- Combinatorial ensemble miRNA target prediction of co-regulation networks with non-prediction data.Nucleic acids research · 2017Article
- Emerging Biosensing Approaches for microRNA Analysis.Analytical chemistry · 2016Review
- Article
- PACCMIT/PACCMIT-CDS: identifying microRNA targets in 3' UTRs and coding sequences.Nucleic acids research · 2015Article
- Strand-specific RNA sequencing in Plasmodium falciparum malaria identifies developmentally regulated long non-coding RNA and circular RNA.BMC genomics · 2015Article
- mirMark: a site-level and UTR-level classifier for miRNA target prediction.Genome biology · 2014Article
- Deletion of microRNA-80 activates dietary restriction to extend C. elegans healthspan and lifespan.PLoS genetics · 2013Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Finding microRNA targets in the coding region is difficult due to the overwhelming signal encoding the amino acid sequence. Here, we introduce an algorithm (called PACCMIT-CDS) that finds potential microRNA targets within coding sequences by searching for conserved motifs that are complementary to the microRNA seed region and also overrepresented in comparison with a background model preserving both codon usage and amino acid sequence. Precision and sensitivity of PACCMIT-CDS are evaluated using PAR-CLIP and proteomics data sets. Thanks to the properly constructed background, the new algorithm achieves a lower rate of false positives and better ranking of predictions than do currently available algorithms, which were designed to find microRNA targets within 3' UTRs.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.