The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations
Open accessAbstract
microRNAs (miRNAs) regulate expression by promoting degradation or repressing translation of target transcripts. miRNA target sites have been catalogued in databases based on experimental validation and computational prediction using various algorithms. Several online resources provide collections of multiple databases but need to be imported into other software, such as R, for processing, tabulation, graphing and computation. Currently available miRNA target site packages in R are limited in the number of databases, types of databases and flexibility. We present multiMiR, a new miRNA-target interaction R package and database, which includes several novel features not available in existing R packages: (i) compilation of nearly 50 million records in human and mouse from 14 different databases, more than any other collection; (ii) expansion of databases to those based on disease annotation and drug microRNAresponse, in addition to many experimental and computational databases; and (iii) user-defined cutoffs for predicted binding strength to provide the most confident selection. Case studies are reported on various biomedical applications including mouse models of alcohol consumption, studies of chronic obstructive pulmonary disease in human subjects, and human cell line models of bladder cancer metastasis. We also demonstrate how multiMiR was used to generate testable hypotheses that were pursued experimentally.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
1 retracted
A TARBP2 mutation in human cancer impairs microRNA processing and DICER1 function
Melo, S. A., Ropero, S., Moutinho, C., Aaltonen, L. A., Yamamoto, H., Calin, G. A., Rossi, S., Fernandez, A. F., Carneiro, F., Oliveira, C., et al. (2009) · Nature Genetics · doi:10.1038/ng.317 · Cited by 373
Self-citationRetractedMicroRNAs: Target Recognition and Regulatory Functions
Bartel, D. P. (2009) · Cell · doi:10.1016/j.cell.2009.01.002 · Cited by 20,068
Most mammalian mRNAs are conserved targets of microRNAs
Friedman, R. C., Farh, K. K.-H., Burge, C. B., & Bartel, D. P. (2009) · Genome Research · doi:10.1101/gr.082701.108 · Cited by 8,462
limma: Linear Models for Microarray Data
Smyth, G. K. (2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0_23 · Cited by 5,796
affy—analysis of Affymetrix GeneChip data at the probe level
Gautier, L., Cope, L., Bolstad, B. M., & Irizarry, R. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg405 · Cited by 5,218
miRBase: tools for microRNA genomics
Griffiths-Jones, S., Saini, H. K., van Dongen, S., & Enright, A. J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm952 · Cited by 4,382
Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt
Durinck, S., Spellman, P. T., Birney, E., & Huber, W. (2009) · Nature Protocols · doi:10.1038/nprot.2009.97 · Cited by 4,197
MicroRNA Targeting Specificity in Mammals: Determinants beyond Seed Pairing
Grimson, A., Farh, K. K.-H., Johnston, W. K., Garrett-Engele, P., Lim, L. P., & Bartel, D. P. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.06.017 · Cited by 3,766
Bioinformatics and Computational Biology Solutions Using R and Bioconductor
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0 · Cited by 3,289
The microRNA.org resource: targets and expression
Betel, D., Wilson, M., Gabow, A., Marks, D. S., & Sander, C. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm995 · Cited by 2,503
Cited by
A multi-organ chip with matured tissue niches linked by vascular flow
Ronaldson-Bouchard, K., Teles, D., Yeager, K., Tavakol, D. N., Zhao, Y., Chramiec, A., Tagore, S., Summers, M., Stylianos, S., Tamargo, M., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-022-00882-6 · Cited by 512
Discovering the 3′ UTR-mediated regulation of alpha-synuclein
Marchese, D., Botta-Orfila, T., Cirillo, D., Rodriguez, J. A., Livi, C. M., Fernández-Santiago, R., Ezquerra, M., Martí, M. J., Bechara, E., Tartaglia, G. G., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx1048 · Cited by 45
14q32 and let-7 microRNAs regulate transcriptional networks in fetal and adult human erythroblasts
Lessard, S., Beaudoin, M., Orkin, S. H., Bauer, D. E., & Lettre, G. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy051 · Cited by 38
Pounders, J., Hill, E. J., Hooper, D., Zhang, X., Biesiada, J., Kuhnell, D., Greenland, H. L., Esfandiari, L., Timmerman, E., Foster, F., et al. (2022) · Medicine · doi:10.1097/md.0000000000030854 · Cited by 26
Tate, M., Wijeratne, H. R. S., Kim, B., Philtjens, S., You, Y., Lee, D., Gutierrez, D. A., Sharify, D., Wells, M., Perez‐Cardelo, M., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.14243 · Cited by 21
Metadata
- Authors
- Ru, Y., Kechris, K. J., Tabakoff, B., Hoffman, P., Radcliffe, R. A., Bowler, R., Mahaffey, S., Rossi, S., Calin, G. A., Bemis, L., & Theodorescu, D.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-07-25
- Volume
- 42
- Issue
- 17
- Pages
- e133-e133
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W1972898510
- Cited by
- 800
- References
- 45
- FWCI
- 3.50
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations. https://app.cochat.ai/papers/10.1093/nar/gku631
- The paper
- Ru, Y., Kechris, K. J., Tabakoff, B., Hoffman, P., Radcliffe, R. A., Bowler, R., Mahaffey, S., Rossi, S., Calin, G. A., Bemis, L., & Theodorescu, D. (2014). The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations. Nucleic Acids Research. https://doi.org/10.1093/nar/gku631
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
