Literature DB >> 27153600

CellMiner Companion: an interactive web application to explore CellMiner NCI-60 data.

Sufang Wang1, Michael Gribskov1, Tony R Hazbun2, Pete E Pascuzzi3.   

Abstract

UNLABELLED: The NCI-60 human tumor cell line panel is an invaluable resource for cancer researchers, providing drug sensitivity, molecular and phenotypic data for a range of cancer types. CellMiner is a web resource that provides tools for the acquisition and analysis of quality-controlled NCI-60 data. CellMiner supports queries of up to 150 drugs or genes, but the output is an Excel file for each drug or gene. This output format makes it difficult for researchers to explore the data from large queries. CellMiner Companion is a web application that facilitates the exploration and visualization of output from CellMiner, further increasing the accessibility of NCI-60 data.
AVAILABILITY AND IMPLEMENTATION: The web application is freely accessible at https://pul-bioinformatics.shinyapps.io/CellMinerCompanion The R source code can be downloaded at https://github.com/pepascuzzi/CellMinerCompanion.git CONTACT: ppascuzz@purdue.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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Year:  2016        PMID: 27153600     DOI: 10.1093/bioinformatics/btw162

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  5 in total

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Journal:  Mol Oncol       Date:  2019-03-01       Impact factor: 6.603

2.  A showcase study on personalized in silico drug response prediction based on the genetic landscape of muscle invasive bladder cancer.

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Journal:  Dis Markers       Date:  2022-09-30       Impact factor: 3.464

4.  Identification of a Metabolic Reprogramming-Associated Risk Model Related to Prognosis, Immune Microenvironment, and Immunotherapy of Stomach Adenocarcinoma.

Authors:  Yan Zhao; Dongsheng Zhang; Yueming Sun
Journal:  J Oncol       Date:  2022-09-21       Impact factor: 4.501

5.  A Novel Gene Prognostic Signature Based on Differential DNA Methylation in Breast Cancer.

Authors:  Chunmei Zhu; Shuyuan Zhang; Di Liu; Qingqing Wang; Ningning Yang; Zhewen Zheng; Qiuji Wu; Yunfeng Zhou
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  5 in total

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