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To predict transcripts for laccase encoding genes, the WISE2 algorithm was used (http://www.ebi.ac.uk/Tools/psa/genewise/).ac.uk/Tools/psa/genewise/
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The traditional approach to address this problem is to perform transcriptome assemblies to obtain predicted transcripts for the two organisms separately (see Figure 1).
The traditional approach to address this problem is to perform de novo transcriptome assemblies to obtain predicted transcripts for these organisms independently and then employ similarity comparison algorithms to study them.
Finally, we examined predicted transcripts for their impacts on peptide sequence to confirm genes where an insertion or deletion can change the amino acid sequence or alternate splice products that differentiate between the two species.
We used exon array data across different tissues (available on the Affymetrix website http://www.affymetrix.com/) to roughly determine whether a gene was expressed in a specific tissue before we selected predicted transcripts for validation.
Additional file 9: Distribution of small RNAs across predicted transcripts for genes with high expression levels.
We aligned Illumina reads to Amel_4.5 in two groups, nurse and forager, using Tophat version 1.3.1 with the option "--butterfly-search" for more spliceive splice junction detection, and then generated predicted transcripts for each set of pooled data using Cufflinks version 1.0.3 with default parameters.
An Affymetrix GeneChip whole genome tiling array was designed, and analyzed at the gene and exon level analysis with a total of 524,909 sense strand probes (average of 16 probes per gene), based on gene model predicted transcripts for T. pseudonana, version 3.0 (http://genome.jgi-psf.org/Thaps3/Thaps3.home.html).html
Using published algorithms to predict target transcripts for these miRNAs, we identified putative target transcripts of the 63-set, which were in turn subjected to pathway analysis.
Reads were also mapped to the predicted transcripts to account for splicing events.
Frequently, the time point of expression is difficult to predict, e.g., for transcripts of high relevance for developmental regulation.
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