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The present work deals with the implementation of a fast annotation system which is able to cluster GO terms on the basis of their semantic similarity and their calculated weights.
Our tests have shown that Sma3s is a fast annotation method requiring minimal human supervision and computational resources.
DAVID was used for further analysis of a panel of differentially expressing genes, which allowed us to perform a fast annotation of genes of interest and to combine them into functional groups.
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Tentative pulse and sine song were detected using a MATLAB script [ 44] and corrected manually in a custom-written user interface allowing fast annotation of sound oscillograms.
On the other hand, RVM can give a sparse solution which is preferred in large data analysis and fast annotation.
Our methodology will help in rapid assembly, fast annotation and reliable prediction of ES proteins.
Automated gene predictions offer fast annotation of genomes but they are error-prone and need to be followed up by careful manual curation of the coding sequences.
Automated protein predictions offer fast annotation but they are error-prone and need to be followed up by careful manual curation.
We have developed Sma3s, a fast, accurate and flexible annotation tool specifically designed for the annotation of large collections of sequences obtained from diverse gene libraries or coding sequence datasets.
To satisfy all of these needs, we have developed a fast method called ARGOT (Annotation Retrieval of Gene Ontology Terms) that is able to interpret the "GO dialect" and analyze hundreds of sequences very rapidly.
Each protein obtained from the IntAct database was identified by a unique UniProt accession number, which enabled a fast collection of GO annotation data from the Uniprot Retrieval System [ 37, 41] (Uniprot protein data obtained on Oct. 1st, 2007).
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