Believe it or not: how much can we rely on published data on potential drug targets?
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A survey on data reproducibility in cancer research provides insights into our limited ability to translate findings from the laboratory to the clinicA living document: reincarnating the research articleDeep impact: unintended consequences of journal rankImproving basic and translational science by accounting for litter-to-litter variation in animal modelsAddgene: making materials sharing "science as usual"Rescuing US biomedical research from its systemic flawsDrug development: Raise standards for preclinical cancer researchThe Rules of the Game Called Psychological ScienceScience or Art? How Aesthetic Standards Grease the Way Through the Publication Bottleneck but Undermine ScienceAchieving human and machine accessibility of cited data in scholarly publicationsAn open investigation of the reproducibility of cancer biology researchEstrogen receptor alpha gene amplification in breast cancer: 25 years of debateModulation of the cancer cell transcriptome by culture media formulations and cell densityEmerging trends in peer review-a surveyRedrawing the frontiers in the age of post-publication reviewWhen are results too good to be true?Data submission and quality in microarray-based microRNA profilingReplication, Communication, and the Population Dynamics of Scientific DiscoveryExamining the Predictive Validity of NIH Peer Review ScoresResearcher perspectives on publication and peer review of dataFacial masculinity: how the choice of measurement method enables to detect its influence on behaviourWhen Quality Beats Quantity: Decision Theory, Drug Discovery, and the Reproducibility CrisisSHRINE: enabling nationally scalable multi-site disease studiesHow to make more published research trueReproducible Research Practices and Transparency across the Biomedical LiteraturePublishing confirming and non-confirming dataAn open science peer review oathBridging the gap between basic and applied biology: towards preclinical translationDo stroke models model stroke?Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule dataEditorial: preclinical data reproducibility for R&D - the challenge for neuroscienceehavioral GeneticsNIH Peer Review: Scored Review Criteria and Overall ImpactRetractions of scientific publications: responsibility and accountabilityIrreproducible Experimental Results: Causes, (Mis)interpretations, and ConsequencesFrequency of discrepancies in retracted clinical trial reports versus unretracted reports: blinded case-control studyIdentification of new epilepsy treatments: issues in preclinical methodologyCommon misconceptions about data analysis and statisticsLost in Translation (LiT): IUPHAR Review 6Acute alcohol response phenotype in heavy social drinkers is robust and reproducible
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Believe it or not: how much can we rely on published data on potential drug targets?
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2011 nî lūn-bûn
@nan
2011 թուականի Օգոստոսին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի օգոստոսին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Believe it or not: how much can we rely on published data on potential drug targets?
@ast
Believe it or not: how much can we rely on published data on potential drug targets?
@en
type
label
Believe it or not: how much can we rely on published data on potential drug targets?
@ast
Believe it or not: how much can we rely on published data on potential drug targets?
@en
prefLabel
Believe it or not: how much can we rely on published data on potential drug targets?
@ast
Believe it or not: how much can we rely on published data on potential drug targets?
@en
P2093
P3181
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Believe it or not: how much can we rely on published data on potential drug targets?
@en
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10.1038/NRD3439-C1
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2011-08-31T00:00:00Z
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1043261616