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Vartika Bisht

Researcher at University of Birmingham

Publications -  5
Citations -  1338

Vartika Bisht is an academic researcher from University of Birmingham. The author has contributed to research in topics: Cancer & Odds ratio. The author has an hindex of 3, co-authored 5 publications receiving 779 citations.

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Journal ArticleDOI

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

TL;DR: This study compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project between March 18 and May 8, 2020 with a parallel non-COVID-19 UK cancer control population, and analyzed the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 prevalence and the case–fatality rate during hospital admission.
Book ChapterDOI

Translational biomarkers in the era of precision medicine.

TL;DR: The past, present and future of clinical biomarker development is discussed, including the identification of physicochemical assays, current regulations, the development and reproducibility of clinical trials, as well as the revolution of omics technologies and state-of-the-art integration and analysis approaches.
Journal ArticleDOI

Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer.

TL;DR: In this article, the authors used public omics data sets to investigate potential associations between microbiome, metabolome, bulk transcriptomics and single cell RNA sequencing datasets, and identified multiple potential interactions, for example 5aminovalerate interacting with Adlercreutzia; cholesteryl ester interacting with bacterial genera Staphylococcus, Blautia and Roseburia.
Journal ArticleDOI

NFnetFu: A novel workflow for microbiome data fusion.

TL;DR: Bisht et al. as mentioned in this paper developed a multimodal framework that considers sparsity (excessive zeros), lower effect size, intrinsically microbial correlations, as well as background biomedical knowledge in the form of a cluster-infused enriched network architecture.