Sentence examples for marker when used from inspiring English sources

ART5 a closely linked marker when used a 200 bp fragment of SUB1 found in the promoter region of SUB1C in 11 rice genotypes such as Swarna-Sub1, IR64-Sub1, SambaMahsuri-Sub1, INGR08110, INGR08110, AC258830, AC42088, AC20431-W, INGR08109, INGR08111 and FR13A (Table 1, please see Additional file 1: Figure S1 and Additional file 2: Figure S2).

We examined whether a combination of miR-141 and CEA was more sensitive than either marker when used individually.

Using several of these methods, we are able to detect HCC in the background of cirrhosis with a predictive probability of at least 0.95, a significant improvement relative to that of any marker when used alone.

This result suggests a higher sensitivity of serum AFP as a tumor marker when used in patients with HBV, but maybe less so in screening patients with HCV for cancer.

Multivariate analysis of the 21 gene set indicated that it was not an independent prognostic marker when used in combination with nodal status or stage for prediction of outcome in our tumor set (data not shown).

I.V.-injected high molecular-weight dextran-FITC (250 kDa) served as a pool marker when using a long pass filter (Ex460-490/Em510 nm).

However, the fact that NMP22 might be a test offering more additional information than other markers when used in combination with cytology has also been observed before [ 28, 29].

In this context, SNPs can be as informative as multiallelic molecular markers when used as "haplotype tags", that is, several SNPs (usually two to four) that tag all the detected haplotypes in a given locus [ 1, 38].

While the four common tumor markers when used individually has little clinical value in the diagnosis of gastric cancer, with the help of the ROC curve analysis and logistic regression analysis, we could determine the optimal cut-off values of the markers and improve the diagnosis of gastric cancer based on these markers.

In terms of the algorithms used to make predictions in CIMMYT trials, no one prediction model fits all situations (trait environment combinations), yet empirical evidence shows that models that include nonlinear functions of the markers, when used on complex traits (that is, grain yield), tend to increase prediction ability as compared with linear models.

Since there is no need to introduce external markers when using this kind microprobe to conduct Raman detection, the information from the cell itself and its chemical response to the environment can be obtained accurately and conveniently [23 25].