Figure 3 Examples of gene expression heterogeneity

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Figure 1 Number of somatic mutation rates across The Cancer Genome Atlas (TCGA) projects Figure 1 | Number of somatic mutation rates across The Cancer.

Figure 2 Enteroids can model transport physiology

promotes the oncogenic activity of CagA

Fig. 8. Recurrent copy number amplification of BRD4 gene was observed across common cancers. Recurrent copy number amplification of BRD4 gene was observed.

Figure 4 Activation of clopidogrel via cytochrome P450

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Figure 1 Patients cured of HCV infection

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Figure 1 Worldwide incidence of CCA

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Figure 1 Biosimilar development process

Figure 2 Effect of PPIs on gastric physiology

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Figure 4 Giant lipid droplet formation

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Figure 2 The association between CD8+ T‑cell density of the tumour

Figure 6 Combination therapy for HCC

Figure 2 Modelling the effect of HCV treatment on reinfection in people who inject drugs Figure 2 | Modelling the effect of HCV treatment on reinfection.

Figure 4 Proinflammatory immune cells and their crosstalk in patients with IBD Figure 4 | Proinflammatory immune cells and their crosstalk in patients.

Figure 1 Definition and concept of ACLF

Figure 2 Switching of biologic agents and biosimilars

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Figure 3 Example wireless motility recording

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to the liver and promote patient-derived xenograft tumour growth

Figure 7 Example colonic high-resolution manometry

Figure 1 Environmental factors contributing to IBD pathogenesis

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Figure 2 13C-octanoic acid gastric emptying breath test

in the UK (1961–2012), France (1961–2014) and Italy (1961–2010)

Figure 2 Key features of gastric cancer subtypes according to The Cancer Genome Atlas (TCGA) Figure 2 | Key features of gastric cancer subtypes according.

Figure 4 Diverse molecular mechanisms of long non-coding RNAs

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Figure 2 Frequency and overlap of alterations

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Figure 6 Assessment of colonic transit time with radiopaque markers

Distribution of intrinsic subtypes among TNBC and distribution of TNBC among basal-like breast cancer. Distribution of intrinsic subtypes among TNBC and.

Figure 5 Systems biological model of IBS

Figure 4 Local species pools that contribute to the

Integrated genomic characterization of oesophageal carcinoma

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Figure 2 Lifelong influences on the gut microbiome from

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Relative expression levels of known mRNA selected as points of reference. Relative expression levels of known mRNA selected as points of reference. mRNA.

Figure 8 Assessment of colonic tone using a barostat device

DNMT3A2 signatures are coherently modified in AML.

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Figure 1. Identification of differentially expressed messenger RNAs (mRNAs) in the The Cancer Genome Atlas (TCGA) BRCA database. (A) Heat map of the log2-fold.

Fig. 3 Transcriptional correlates of improved health in TRF

Figure 1 The spread of colorectal cancer metastases

RNA-seq analysis from the MVI-it culture indicates that a majority of the BGHV8 coding sequences are transcribed. RNA-seq analysis from the MVI-it culture.

A, Proportion of variants detected in the MMR genes.

Frequently mutated genes in colorectal cancer.

PTEN genotype frequently dictates PTEN expression status, but evidence of heterogeneous staining implies polyclonality within some ovarian tumors. PTEN.

Integrated analysis of gene expression and copy number alterations.

Genomic instability is a core feature of ovarian cancer that frequently involves DNA-damage repair genes. Genomic instability is a core feature of ovarian.

TME characteristics of TCGA-STAD subtype and cancer somatic genome.

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Figure 3 Examples of gene expression heterogeneity in epigenome regulators among the TCGA gastric cancer subtypes Figure 3 | Examples of gene expression heterogeneity in epigenome regulators among the TCGA gastric cancer subtypes. a | Numbers indicate average reads per kilobase per million mapped reads (RPKM) values. Colour code represents relative transcript levels (red, high; green, low). Epstein–Barr virus (EBV), n = 25; microsatellite instability (MSI), n = 64; chromosomal instability (CIN), n = 142; genomically stable (GS), n = 60. b | TET1 mRNA levels in the four TCGA subtypes. This figure was generated using publicly accessible data from The Cancer Genome Atlas147. Padmanabhan, N. et al. (2017) How to stomach an epigenetic insult: the gastric cancer epigenome Nat. Rev. Gastroenterol. Hepatol. doi:10.1038/nrgastro.2017.53