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By using computational prediction and recombinant human proteasome catalytic subunit β1, we found in the present study that proteasome catalytic subunit β1 could serve as a direct target of celastrol.
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The significant overlap between our computational predictions and RNAi screening results suggests that RNAi screen results can be improved by using computational predictions to guide experiments, performing RNAi screens in size-reduced, prioritized subspaces predicted by our model, thus allowing more tissue types or experimental conditions to be tested with the same resources.
The miRNA targets have been extensively investigated in Arabidopsis and rice using computational prediction, experimental validation by overexpression in transgenic plants, and by degradome or PARE (parallel analysis of RNA ends) sequencing.
However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%).
Here, we have taken the eQTL mapping paradigm to the single nucleotide level by predicting specific nucleotide differences that cause gene expression divergence using computational predictions of TFBSs.
Class I and II transposon sequences were initially identified by searching among the repetitive sequences for putative transposon elements using computational predictions based on BLASTX analysis.
By using computational target prediction algorithm miRBase [ 46], we screen out all the potential target genes of miR369-3; all of them are not directly in the pathway given in Tyson's model.
We thus used computational prediction to identify candidates for further testing.
This gap can be partially filled by using computational protein structure prediction.
What is more, by using computational mutagenesis, rational protein design, and the prediction of structures-proteins function relationship, it will be possible to study the structure of NCAN, VCAN, or ACAN mutants which are able or not to induce neurodevelopment disorders.
Using computational target prediction software we have identified differentially expressed miRNAs associated with muscle hypertrophy.
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