Sentence examples for mutation profiles from from inspiring English sources

First, the somatic mutation profiles from both the COSMIC and TCGA are mixed with driver and passenger mutations.

Using a hierarchical clustering of gene mutation profiles from an ovarian cancer dataset, we demonstrate the use of the method as a feature selection tool.

In this study, we sought to evaluate the putative drug sensitivity genes by incorporating drug pharmacological data, protein pocket information, and cancer cell line mutation profiles from the CCLE.

DriverDB is a web resource that includes mutation profiles from 6079 tumor-normal pairs (4397 from TCGA, 861 from ICGC, 112 from PCGP, 238 from TARGET and 471 from published papers) of 14 different cancer types and exploits eight computational methods to identify driver cancer genes for each tumor type.

Espinosa et al. [ 21] proposed a predictor, InCa (Index of Carcinogenicity) that integrates somatic mutation profiles from the Catalogue of Somatic Mutations in Cancer (COSMIC) database and the neutral mutations from the 1000 Genomes project into protein structure and interaction interface information.

We sought to characterize the extent of clonal branching involving key tumor suppressor mutations in primary ccRCC and determine if genetic heterogeneity could limit the mutation profiling from a single region assessment.

The presented results of this study may, in the future, lead to the development of nanomaterial-based device for the detection of the genetic mutation profile from the headspace of a lung cancer tissue specimen obtained through biopsy, or from patients' breath.

In the next step, GWAMAR computes binary mutation profiles for each mutation profile.

Except for one new mutation profile originating from a synthetic construct (GI 151861), all new mutation profiles originated from microbial sources.

Most of the novel mutation profiles originate from artificial constructs such as cloning vectors, and hence do not qualify for the assignment of a new TEM number.

For the HIV dataset, we classify viral reverse transcriptase sequences as resistant or susceptible against eight nucleoside analogs using mutation profiles extracted from sequence information of the viral genotype.