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Karen A. Ryall

dblp:159/4716 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 91% Medical and health informatics · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
cancer genomics
0.212015
Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data · Bioinform. 2015
Bioinformatics and computational biology › drug discovery
drug repurposing
0.212015
DSigDB: drug signatures database for gene set analysis · Bioinform. 2015
Bioinformatics and computational biology › functional genomics › functional enrichment analysis
gene set enrichment analysis
0.212015
DSigDB: drug signatures database for gene set analysis · Bioinform. 2015
Medical and health informatics › precision medicine
targeted therapy
0.112015
Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data · Bioinform. 2015

Methods — techniques the papers use, named apart from their topics

gene set enrichment analysis · 0.2
YearPublicationVenuePosition
2015 Identifying kinase dependency in cancer cells by integrating high-throughput drug screening and kinase inhibition data
abstract
MOTIVATION: Targeted kinase inhibitors have dramatically improved cancer treatment, but kinase dependency for an individual patient or cancer cell can be challenging to predict. Kinase dependency does not always correspond with gene expression and mutation status. High-throughput drug screens are powerful tools for determining kinase dependency, but drug polypharmacology can make results difficult to interpret. RESULTS: We developed Kinase Addiction Ranker (KAR), an algorithm that integrates high-throughput drug screening data, comprehensive kinase inhibition data and gene expression profiles to identify kinase dependency in cancer cells. We applied KAR to predict kinase dependency of 21 lung cancer cell lines and 151 leukemia patient samples using published datasets. We experimentally validated KAR predictions of FGFR and MTOR dependence in lung cancer cell line H1581, showing synergistic reduction in proliferation after combining ponatinib and AZD8055. AVAILABILITY AND IMPLEMENTATION: KAR can be downloaded as a Python function or a MATLAB script along with example inputs and outputs at: http://tanlab.ucdenver.edu/KAR/. CONTACT: [email protected]. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Karen A. Ryall, Jimin Shin, Minjae Yoo, Trista K. Hinz, Jihye Kim 0004, Jaewoo Kang, Lynn E. Heasley, Aik Choon Tan
Bioinform.1
2015 DSigDB: drug signatures database for gene set analysis
abstract
UNLABELLED: We report the creation of Drug Signatures Database (DSigDB), a new gene set resource that relates drugs/compounds and their target genes, for gene set enrichment analysis (GSEA). DSigDB currently holds 22 527 gene sets, consists of 17 389 unique compounds covering 19 531 genes. We also developed an online DSigDB resource that allows users to search, view and download drugs/compounds and gene sets. DSigDB gene sets provide seamless integration to GSEA software for linking gene expressions with drugs/compounds for drug repurposing and translational research. AVAILABILITY AND IMPLEMENTATION: DSigDB is freely available for non-commercial use at http://tanlab.ucdenver.edu/DSigDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: [email protected].
Minjae Yoo, Jimin Shin, Jihye Kim 0004, Karen A. Ryall, Kyubum Lee, Sunwon Lee, Minji Jeon, Jaewoo Kang, Aik Choon Tan
Bioinform.4