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Shivangi Wani

Researcher at University of Queensland

Publications -  21
Citations -  9395

Shivangi Wani is an academic researcher from University of Queensland. The author has contributed to research in topics: Cancer & Gene expression profiling. The author has an hindex of 15, co-authored 21 publications receiving 7855 citations. Previous affiliations of Shivangi Wani include QIMR Berghofer Medical Research Institute.

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Genomic analyses identify molecular subtypes of pancreatic cancer

Peter Bailey, +128 more
- 03 Mar 2016 - 
TL;DR: Detailed genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing.
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Whole genomes redefine the mutational landscape of pancreatic cancer.

Nicola Waddell, +88 more
- 26 Feb 2015 - 
TL;DR: Genomic instability co-segregated with inactivation of DNA maintenance genes (BRCA1, BRCA2 or PALB2) and a mutational signature of DNA damage repair deficiency, and 4 of 5 individuals with these measures of defective DNA maintenance responded to platinum therapy.
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Pancreatic cancer genomes reveal aberrations in axon guidance pathway genes

Andrew V. Biankin, +140 more
- 15 Nov 2012 - 
TL;DR: It is found that frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, are also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement ofAxon guidance genes in pancreatic carcinogenesis.
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Stem cell transcriptome profiling via massive-scale mRNA sequencing.

TL;DR: A massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, is developed, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that the understanding of transcriptional complexity is far from complete.