ライフサイエンスコーパス: mutation pattern

1 f the non-RS transgenes without altering the mutation pattern.

2 from a target region with a dense and unique mutation pattern.

3 an colon cells, it induces a bacteria-unique mutation pattern.

4 e stringent criteria indicative of an APOBEC mutation pattern.

5 nships between flanking base composition and mutation pattern.

6 ified by germ-line gene usage and junctional mutation patterns.

7 zed by specific gene expression profiles and mutation patterns.

8 e histories of individual HSCs using somatic mutation patterns.

9 ), but this alone does not explain the tumor mutation patterns.

10 ne expression patterns and pathologic driver mutation patterns.

11 tion in specific genomic regions and somatic mutation patterns.

12 selection pressures, which skew the observed mutation patterns.

13 e SHM process and support future analyses of mutation patterns.

14 l tumors, we observed three distinct somatic mutation patterns.

15 (BASELINe) based on the analysis of somatic mutation patterns.

16 or age groups for specific three-dimensional mutation patterns.

17 d NNRTI-resistance mutations, with divergent mutation patterns.

18 joining and mismatch repair do not influence mutation patterns.

19 ed glycosylation sites, and isolate-specific mutation patterns.

20 Specific co-mutation patterns account for clinical heterogeneity wit

21 Driver genes with a mutually exclusive mutation pattern across tumor genomes are thought to hav

22 occurring and mutually exclusive driver gene mutation patterns across cancer genomes and discuss thei

23 The APOBEC mutation pattern also extended to cancer-associated gene

24 Substantial variability in mutation pattern among loci was found, most of which can

25 The similarity of mutation pattern among triple repeat-related diseases in

26 Our work reveals a bacteria-specific mutation pattern and suggests that the resistance protei

27 BRAF V600E and TERT promoter mutation patterns and associated patient deaths caused b

28 s and Measures: BRAF V600E and TERT promoter mutation patterns and associated patient deaths caused b

29 They capture somatic mutation patterns and at best identify their causes.

30 d signaling, that may promote these distinct mutation patterns and differential coupling to specific

31 a canonical pathway with mutually exclusive mutation patterns and distinct biological functions.

32 for efficient and reliable identification of mutation patterns and driver pathways in large-scale can

33 However, certain changes in mutation patterns and frequency of point mutations were

34 Altered mutation patterns and Igh architectural defects in DIS3-

35 prostate, characterized localized passenger mutation patterns and may reflect tumor-cell-of-origin i

36 the existing systematic guidelines regarding mutation patterns and molecular biomarkers, resulting in

37 Such damage can produce strand-phased mutation patterns and multiallelic variation through the

38 us, genome-wide correlations between somatic mutation patterns and normal cell transcription may refl

39 Mutation patterns and OS differed between the 84 patient

40 lan of key experiments from "Diverse somatic mutation patterns and pathway alterations in human cance

41 the distinct biases inherent in the initial mutation patterns and subsequent evolutionary processes

42 Different mutation patterns and variant allele frequencies (VAFs)

43 er cytosines or guanines in the same strand, mutation patterns, and genetic controls indicated that s

44 cesses to orphan and newly discovered tumour mutation patterns, and to determine whether avoidable ca

45 d in many tumors, but factors affecting this mutation pattern are not well understood.

46 hen the proper statistical properties of the mutation pattern are used to interpret the readouts.

47 Some mutation patterns are clearly attributable to disruption

48 We further demonstrate that strand-specific mutation patterns arise from some of these POLE-exo* mut

49 ighly favored (or entrenched) by the complex mutation patterns arising in response to drug therapy de

50 I have studied mutation patterns around very short microsatellites, foc

51 We observed a mutation pattern associated with altered CpGs and APOBEC

52 however, is hampered by the large numbers of mutation patterns associated with cross-resistance withi

53 s in Smu- and Sdelta-like (sigma(delta)) nor mutation patterns at Smu-sigma(delta) junctions.

54 Mutation patterns at virologic failure were in line with

55 By studying mutation patterns based on 985,069 mutations obtained fr

56 ole-exome sequencing revealed differences in mutation patterns between control and irradiated tumors,

57 Four factors determine the residue type mutation patterns: biases in the germline, accessibility

58 ithin introns are consistent with changes in mutation patterns, but stronger GC elevation at synonymo

59 These mutation pattern changes in Brca2-deficient B cells were

60 l selection or CCR5 inhibition have a common mutation pattern characterized by the same two V3 mutati

61 hypotheses tried to explain such significant mutation patterns, conclusive explanations are lacking.

62 In light of the mutation pattern consistent with dCMP insertion observed

63 ells were hypermutated at low frequency with mutation patterns consistent with A3F activity.

64 We observed several mutation patterns consistent with previous studies, such

65 ted ancestral histories of RNA genes contain mutation patterns consistent with the DNA replication-re

66 ated indel signature and a recurrent complex mutation pattern, consisting of both a single-nucleotide

67 Six M(pro) mutation patterns containing T304I alone or in combinati

68 F complex in (N)RAS melanomas, and select co-mutation patterns coordinated selective response to immu

69 No recurrent mutation pattern correlated with unilineage dysplasia wi

70 In addition, we show that another mutation pattern, COSMIC signature 5, is positively asso

71 ene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Ca

72 developed a rigorous methodology for cancer mutation pattern discovery based on a new, constrained f

73 Unique mutation patterns distinguish OV-associated CCA from oth

74 We analyzed gene expression data and mutation patterns, distributions and loads for 19 differ

75 Recurrent mutation patterns exhibited different VAFs associated wi

76 Here we report an analysis of the mutation patterns for 5296 Alu elements comprising 20 su

77 Profiling DNA mutation patterns for cancer classification plays an ess

78 s effectiveness and robustness in predicting mutation patterns for unforeseen mutations, we first des

79 Evaluation of intraclonal mutation patterns identified clone-specific punctuated c

80 The novel mutation patterns identified here imply rational use of

81 Mutation patterns implicate replication infidelity as on

82 ly analyzed the mtDNA control region somatic mutation pattern in 2864 single hematopoietic stem cells

83 showed a significant presence of the APOBEC mutation pattern in bladder, cervical, breast, head and

84 The mutation pattern in the nullizygotes was notable for fre

85 f CS, but we also found differences from the mutation pattern in tumorigenesis.

86 dy, we performed spatial analyses of somatic mutation patterns in 18 DCIS tumors to infer the underly

87 Here we determine genome-wide mutation patterns in ASCs of the small intestine, colon

88 t redundancies can shape tumor-type specific mutation patterns in chromatin regulators.

89 rscore the possibility of distinct molecular mutation patterns in EAC among different races.

90 The ability to detect selection by analyzing mutation patterns in experimentally derived immunoglobul

91 res have been associated with characteristic mutation patterns in genes, the factors that lead to pro

92 We demonstrate that mutation patterns in immortalised cell lines derived fro

93 Differential mutation patterns in known resistance alleles indicated

94 developed a method that analyzes correlated mutation patterns in multiple sequence alignments in ord

95 Analyses of mutation patterns in noncoding DNA suggest that the exte

96 The mutation patterns in one case suggest that the intestina

97 TIgGER analyzes mutation patterns in Rep-Seq data to identify novel V se

98 We show that SPLASH identifies complex mutation patterns in SARS-CoV-2, discovers regulated RNA

99 ne sequences, we have thoroughly studied DNA mutation patterns in the human genome.

100 The mutation patterns in these unexpressed genes are unselec

101 n is secondary to the gastric tumor, and the mutation patterns in two cases indicate that the gastric

102 , and we also report potentially interesting mutation patterns in world populations estimated by mStr

103 A deep understanding of future mutation patterns, in particular the mutations that will

104 ated rate of mutagenesis, eliciting specific mutation patterns including COSMIC signature SBS3.

105 Mutation patterns (including clearance of leukemia-assoc

106 e switch process can create numerous complex mutation patterns, including hairpin loop structures, an

107 Complex mutation patterns, including thymidine-analog mutations,

108 The mutation pattern is defined by a dominant prevalence of

109 The aetiology of this differing mutation pattern is still unknown.

110 data (common and rare variants) and somatic mutations patterns (lower mutation load if compared to y

111 mutations (CH-like cluster) or combinatorial mutation patterns (MN-like cluster), and showing differe

112 tional tools; and uncovers unique co-varying mutation patterns not associated with any known variant.

113 HM in a non-B cell context was compared with mutation patterns observed for SHM in vivo.

114 However, there is discordance between the mutation patterns observed in HIV-infected patients fail

115 The conservation of the c-kit mutation pattern, observed in consecutive lesions from t

116 membrane compartments, and reflective of the mutation pattern of HIV-1.

117 significantly decreased SHM and changed the mutation pattern of the variable region of the immunoglo

118 using a novel typing method to monitor fimH mutation patterns of fecal isolates from adenoma patient

119 inhibitors in combination or in succession, mutation patterns of protease isolates from these person

120 r HOXB expression signatures showed distinct mutation patterns of RAS pathway genes, FLT3 or WT1, sug

121 Here we analyzed the mutation patterns of the PPI interfaces from 10,028 prot

122 The predominant mutation patterns of these tumors also suggest differenc

123 Analyses of Drosophila spontaneous mutations, patterns of segregating variation and covaria

124 th sex-specific life history traits to shape mutation patterns on both the X chromosome and autosomes

125 Furthermore, we find that change in mutation pattern or in tDNA copy number changed codon-us

126 el with hidden states representing different mutation patterns; PSSV can thus differentiate heterozyg

127 Furthermore, we identified asymmetrical mutation patterns reflecting selective pressures exerted

128 ily be adapted to analyze other types of DNA mutation patterns resulting from a mutator that displays

129 In addition, they demonstrate that the mutation pattern seen previously in mismatch repair defe

130 den retrievers, show little overlap in their mutation pattern, sharing only one of their 15 most recu

131 Finally, detailed analysis of mutation patterns showed that strains carrying the B all

132 hared mechanism of mutagenesis that yields a mutation pattern similar to cancer Signature 14.

133 roduced an elevated mutation frequency and a mutation pattern similar to that seen in the tumors.

134 ex (CRC) in human cancer, exhibiting a broad mutation pattern, similar to that of TP53.

135 Mutation patterns strongly implicate ultraviolet radiati

136 clearly enriched for tumors with the APOBEC mutation pattern, suggesting that this type of mutagenes

137 To identify mutation patterns that affect disease phenotype and clin

138 Analysis of the mutation patterns that arise through CAVE iterations elu

139 damage checkpoint also give rise to somatic mutation patterns that can be used for treatment predict

140 (WGS) of human tumors has revealed distinct mutation patterns that hint at the causative origins of

141 vealed driver genes with individually sparse mutation patterns that would not be detectable by other

142 ive power and can be used to predict complex mutation patterns, that have not yet been observed due t

143 By studying virus migration and mutation patterns, the field of phylogeography provides

144 ns shrinks during the accumulation of random mutations-patterns thought to indicate a convex fitness

145 h that clusters co-varying and time-evolving mutation patterns to identify SARS-CoV-2 variants.

146 In so doing, we are able to ascribe specific mutation patterns to replication timing and recombinatio

147 o the generation of specific antibodies with mutation patterns typical of affinity maturation, showin

148 cesses and the extent to which MMR-deficient mutation patterns vary among species.

149 nd GAA sequences in rpsL This characteristic mutation pattern was also observed in the genomic region

150 n the group that secreted both isotypes, the mutation pattern was identical, indicating either synthe

151 tected in 2 (8.3%) neonatal samples, but the mutation pattern was not identical to the mother's.

152 The mutation pattern was similar to that of Ig genes.

153 The mutation pattern was similar to that previously reported

154 d cytopenia, the presence of highly specific mutation patterns was associated with myelodysplastic-li

155 ually high mutation frequency and an altered mutation pattern were seen in xeroderma pigmentosum vari

156 Interestingly, similar mutation patterns were also observed in minor quasispeci

157 tures, DNA copy number patterns, and somatic mutation patterns were highly similar across each primar

158 These Ras mutation patterns were maintained whether oncogenic tran

159 Few differences in mutation patterns were observed before and after treatme

160 Readily interpreted mutation patterns were observed, such as small inversion

161 r mutations, which are representative of the mutation pattern, were selected.

162 gene in that it showed a mutually exclusive mutation pattern when compared with mutations in the Trr

163 s robustness by accurately predicting unseen mutation patterns when training on data from two pattern

164 ximately 25% of AML, with a distinct genetic mutation pattern where >98% of cells are CD34(-), there

165 rmline could inform risk for specific tumour mutation patterns, which could have important translatio

166 story of presence at birth showed an inverse mutation pattern with common BRAF mutations (20/28 or 71

167 Thus, comparing complex mutation patterns with viral fitness may help to elucida

168 ructural and functional significance of this mutation pattern within the context of the complex relat