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The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies

eLife(2020)10.7554/elife.52707Source: DataRank Database

The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies is a research paper published in eLife (2020). On theSindex it has a DataRank of 1.4. It has been cited 41 times, with 37 citing works in its 1-hop citation network.

N/A

1.4DataRank · unranked

Scored on demand from live citation data

Deposits data Open Access41 citations · 37 citing works in its network

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Data availability

Repositories this paper deposited data in (declared in PubMed).

GEOGSE149428

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (19 grants)OA: goldTopics (50)IDs (PubMed)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 41%Citation Network 59%

Base Score Contribution

0.561

From this paper's citation signal

Citation Network Contribution

0.791

From 29 citing papers with measurable signal

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Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 37 citers.

MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores
Bioinformatics202349 citations40 referencesContributes 0.098
Deep neural network prediction of genome-wide transcriptome signatures – beyond the Black-box
npj Systems Biology and Applications202233 citations49 referencesContributes 0.072
A novel network based linear model for prioritization of synergistic drug combinations
PLoS ONE202210 citations34 referencesContributes 0.071
Local generation and efficient evaluation of numerous drug combinations in a single sample
eLife20236 citations34 referencesContributes 0.057
Sophorolipids: Anti-cancer activities and mechanisms
Bioorganic & Medicinal Chemistry202236 citations68 referencesContributes 0.053

Authors (9)

Mehmet Eren Ahsen ORCID,Thomas Schaffter ORCID,Xintong Chen ORCID,Ronald Realubit ORCID,Charles Karan ORCID

Live enrichment

PubMed:32945258

IBM

Grant: IBM Research

National Institutes of Health

Grant: NIH T32 GM007280

National Institutes of Health

Grant: NIH-U54OD020353

National Cancer Institute

Grant: U54 CA209997 (Cancer Systems Biology Consortium)

National Institutes of Health

Grant: S10OD012351 and S10OD021764 (NIH instrumentation grants)

National Institutes of Health

Grant: 1S10OD021764-01

Storage System for High Performance Computing

National Institutes of Health

Grant: 3T32GM007280-38S2

Mount Sinai Medical Scientist Training Program

National Institutes of Health

Grant: 5U54OD020353-02

A New Disease Platform Leveraging Complex Drosophila and Mammalian Models

National Institutes of Health

Grant: 5U54CA209997-05

Centers for Cancer Systems Therapeutics (CaST)

National Institutes of Health

Grant: 1S10OD012351-01

High-performance compute cluster for biomedical computing

National Institutes of Health

Grant: 1S10OD026880-01

Big Omics Data Engine 2 Supercomputer

National Institutes of Health

Grant: 1S10OD018522-01

Transforming Genomics with 5 PB Big Omics Data Engine Cray CS300-AC Supercomputer

NCI NIH HHS

Grant: U54 CA209997

NIH HHS

Grant: S10 OD012351

NIH HHS

Grant: S10 OD021764

NIH HHS

Grant: S10 OD018522

NIH HHS

Grant: S10 OD026880

NIGMS NIH HHS

Grant: T32 GM007280

NIH HHS

Grant: U54 OD020353

goldLicense: cc-by

publisherhttps://doi.org/10.7554/elife.52707

publisherhttps://cdn.elifesciences.org/articles/52707/elife-52707-v2.pdf

publisherhttps://cdn.elifesciences.org/articles/52707/elife-52707-v2.xml

publisherhttps://elifesciences.org/articles/52707

repositoryhttps://doaj.org/article/665260e292954bb886f7e1e6728dbc27

Fields of Study

0301 basic medicine03 medical and health sciences0303 health sciencesAlgorithmsComputational BiologyDrug CombinationsDrug SynergismGene ExpressionGene Regulatory NetworksHumansMCF-7 CellsRNA-SeqTranscription FactorsTranscriptome

MeSH Terms

AlgorithmsComputational BiologyDrug CombinationsDrug SynergismGene ExpressionGene Regulatory NetworksHumansMCF-7 CellsRNA-SeqTranscription FactorsTranscriptome

Keywords

drug synergyQH301-705.5ScienceGene ExpressiontranscriptomicsHumansGene Regulatory NetworksRNA-SeqBiology (General)cancer biologyMCF7LNCaPQRComputational BiologyDrug SynergismCell BiologyDrug CombinationsMCF-7 CellsMedicineTranscriptomeAlgorithmsTranscription Factorshumansystems biology

Sustainable Development Goals

SDG 3: 3. Good health