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Several methods which do not require prior knowledge of marker genes have been developed [61, 83, 84].
In both systems, antibiotic resistance marker genes have been replaced by selection markers (pSIP: alr, alanine racemase gene; NICE: lacF, gene encoding the soluble carrier enzyme IIA of the lactose specific phosphotransferase system) complementing corresponding gene deletions in the host chromosomes.
Since few overlaps have been found among the published breast cancer signatures, it appears that many (thousands) of marker genes have predictive ability in different subsets of patients.
Other individual marker genes have been found of proven validity in this field, such as α-methylacyl coenzyme A racemase (AMACR) [20], [21] or Prostate Cancer Antigen 3 (DD3/PCA3) [22], but at the moment no relationship between the expression level of PCA3 and tumour grade or staging was found yet.
Specific panels of CIMP marker genes have been developed to classify CRCs into these three subclasses.
Antibiotic/ herbicide resistant marker genes have been proven to be very useful in plant transformation for the initial selection of desired transgenic events.
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The expression of SMC marker genes has been shown to be regulated by CArG-SRF complexes, by myocardin and by Myocardin Related Transcription Factors MRTF-A and MRTF-B that induce transcription of SMC marker genes in a CArG dependent manner [1], [2], [3], [4], [5].
The DNA methylation status of entire promoter CpG islands, other than Infinium probe sites, in the CIMP marker genes has not been evaluated quantitatively.
Expression of key matrix genes within tissue engineered constructs has also been used to identify such differentiation, although validation of the relevance of the candidate marker genes has not yet been performed [ 10].
The tumour marker genes had been selected after a systematic search for genes that are highly expressed in breast cancer, but not in the cellular constituents of peripheral blood (Bosma et al, 2002).
We demonstrated that known or potential marker genes had high expression levels on average in 34 of the 36 real experimental datasets and applied our idea as the weight term in the WAD statistic.
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