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The sequence and mutation profiles for the samples using WGA are reported in this study.
In the next step, GWAMAR computes binary mutation profiles for each mutation profile.
The mutation profiles for the libraries prepared by using either old or new primer sets are also highly similar.
Tables 2 and 3 present the top-scored gene gain/loss, and point mutation profiles for the dis-cussed drugs, respectively.
Note: The mutation profiles for the splenic B-1a IgH libraries prepared by using either old (VH12-3 deficient) or new primer set (VH12-3 included) are highly similar.
Now, let V T(n) denote the number of colorings of size n: V T (n ) = # { c ∈ C T : | c | = n } V T(n) may be interpreted as the total number of binary mutation profiles for which the induced coloring is of the same size as for c ¯.
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We now demonstrate the clinical feasibility of mass-spectrometric based cancer gene mutation profiling for a large panel of oncogene and TS gene mutations.
In this study, we adapted genotyping-based mutation profiling for the characterization of both frozen and FFPE-derived tumor specimens spanning 12 cancer types.
Notably, glioblastomas exhibit a different mutation profile for some genes as compared to other tumor types.
The mutation profile for high-risk patients was 90.1% sequencing mutations versus 9.9% LRs, and for elective patients, 94.1% sequencing versus 5.9% LRs.
These inconsistencies, together with two other factors, have limited the impact of mutation profiling for prognosis and prediction in standard care of colon cancer.
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