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BLASTp was used to align both our assembled transcripts and the Ensembl annotated genome annotations against the human RefSeq proteins [ 13].
This annotator was more familiar with the terminology, detected more errors, and created annotations against the terminology more accurately.
The initial build was further subjected to (1) mapping annotations against the Uniprot features and annotations, (2) picking up annotations from KEGG that were missed by our pipeline, (3) second-level pruning for species filters, (4) manual quality control and (5) manual curation of new and existing pathways to integrate rice specific data,and literature citations.
The presented comparisons of AGeS annotations against three annotations systems (JCVI, BCM, and Sanger Institute) indicated differences, which primarily arose from the different annotation tools used in the different systems.
We sought to validate the annotations against the current information for the human genome.
We therefore validated the reporter annotations against the data present in the NCBI Entrez [ 1] database http://www.ncbi.nlm.nih.gov.nih.gov
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For the TE-to-gene BLAST analysis, we sought chimeric TEs directly by querying each canonical TE sequence in version 7.1 of the BDGP TE data set [ 49] that had a representative in the Release 3.1 euchromatic genome annotation against the Release 3.1 annotated transcripts.
Additionally, this work proposes a comparison study of models trained using fully-automatic data acquisition and annotation against models that were partially annotated.
Extensive experiments conducted on three benchmark datasets show that our topic model provides the accurate annotation against the noise and incompleteness of tags.
We performed BLASTX searches for functional annotation against the nonredundant protein database of the NCBI.
We compared each gene MeSHOP with GeneRIF annotation against each disease using the similarity scores.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com