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We defined the target coverage as the number of genes within a pathway that were predicted targets (prediction agreement ≥ 2) of miRNAs residing in host genes within that pathway, over the total number of genes in the pathway.
By using a popular miRNA targets prediction algorithm TargetScan, TGFβR1 was predicted to be a theoretical target of miR-490-3p miR-490-3p miR-490-3pNA recognition element (MRE) in 3′UTR was conserved among mammals.
Several commercially available compound databases for hit identification and a well-annotated pharmacophore database for drug targets prediction were integrated in iDrug as well.
The web interface enables binding sites detection, virtual screening hits identification, and drug targets prediction in an interactive manner through a seamless interface to all adapted packages (e.g., Cavity, PocketV.2, PharmMapper, SHAFTS).
Given that miRNA targets prediction often suffer from high level of false positives, only the target gene supported by at least three independent tools were taken into account.
The subsequent analysis of miRNA targets prediction and target gene functional annotation was performed using the TargetScan software (http://www.targetscan.org/) and the DAVID gene annotation tool (http://david.abcc.ncifcrf.gov/), respectively.
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Target-align [ 29], a miRNA target prediction tool, was used to predict putative miRNA target genes.
To increase the stringency of the target prediction protocol, we searched for mRNAs simultaneously predicted by five or more different target-prediction programs.
We identified predicted target genes of miR-218 using four online miRNA target prediction algorithms.
Target prediction for plant microRNAs.
Fig. 3 Target prediction and intersection.
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