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We have developed bioinformatics workflows capable of using these datasets to further annotate each cell line, including the cell line origin, 4-digit HLA types [ 6], gene expression levels, expressed viruses, and mutations.
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We use these datasets to describe both the architecture (structure) of world-class gold systems of the Yilgarn Craton and the signatures of their formation.
We used these datasets to demonstrate the runtime and power of EPIQ under different conditions.
We used these datasets to explore and provide new insights into metazoan adaptation, diversity and evolution.
We use these datasets to compare the performance of PDEGEM with the Poisson-Linear model and MART method implemented in mseq.
We used these datasets to compute the true correlation between the predicted and the true breeding values, true heritability as the square of the correlation between the predicted and the true breeding values and estimates of heritability for each of four different indirect methods.
Thus all work presented in this paper is performed using these datasets, limiting generalizability to different types of cancer.
Using these datasets, it is possible to ask: are the associated SNPs, or flanking DNA, linked with the expression of another gene in the region?
The amount of information you can find out about someone using these datasets can be astounding".
Moreover, we present a Web-based service that uses these datasets in order to assist with the completion of risk assessment forms.
Permission to use these datasets was obtained through application to dbGAP by B.T.H.
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CEO of Professional Science Editing for Scientists @ prosciediting.com