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Further cleaning of the dataset looked for logical errors, out of range responses and duplications.
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It operates by comparing each paragraph with every other paragraph in the dataset looking for the most similar one and each term in a paragraph is given the same weight.
Use the endogenous polarity chunks to perform a maximum forward matching segmentation on the given Plurk training dataset, looking for chunks with polarities of higher confidence levels and of the longest length first.
Despite this resource, in order to build a more complete feature set from each message, the following procedures are considered for the generated endogenous polarity chunks: 1. Use the endogenous polarity chunks to perform a maximum forward matching segmentation on the given Plurk training dataset, looking for chunks with polarities of higher confidence levels and of the longest length first.
In fact the kNN algorithm searches through all the dataset looking for the most similar instances.
Our results show that a qualitative comparison of proteomic and transcriptomic datasets, looking for homodirectional changes between among gene products common to these datasets, has value in identifying novel regulatory connections.
We reanalysed recently published (Kobayashi et al., 2012; Smallwood et al., 2011) datasets looking for CGIs that: (1) were completely methylated (>75%) in wild-type (WT) meiosis II (MII) oocytes; (2) were significantly methylated in blastocysts; and (3) lost >50% methylation in DNMT3L-deficient oocytes.
For each dataset we looked for the processed sequence along with its cloning frequency.
To determine the major biological themes found in this dataset, we looked for Gene Ontology (GO) classifications that were over-represented in these two gene lists using GOEAST [ 12].
Using the combined datasets, we looked for genes that showed high expression and high levels of H3K4me3 in the normal colon samples, and were repressed in any one of the five colon cancer cell lines; 1,085 genes fit these criteria.
In order to integrate the duplicated synteny anchors in the dataset, we first looked for the bounds of the duplicated part, then we reintroduced all deleted synteny anchors yielding two juxtaposed identical parts, and finally collapsed the synteny anchors involved in the two parts by re-numbering them to obtain the part before tandem duplication.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com