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Engineering threshold-based selection systems

UNC Libraries(2022)10.17615/qf66-d592Source: DataRank Database

Engineering threshold-based selection systems is a research paper published in UNC Libraries (2022). On theSindex it has a DataRank of 0.

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Scored on demand from live citation data

Open Access0 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

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Enrichment:Funding (4 grants)Impact (FWCI 0.00)OA: greenTopics (15)IDs (PubMed, OpenAlex)

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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Authors (8)

K.H. Pedone,A.D. Cox,S. Ahmed,L.E. Leopold,D.J. Reiner

Live enrichment

PubMed:19767382 OpenAlex:https://openalex.org/W4287487037

National Institutes of Health

Grant: 5R01CA175747-05

Mechanisms of PAK1 activation, signaling and tumor resistance

National Institutes of Health

Grant: 5T32CA009156-20

BASIC MECHANISMS OF VIRAL AND CHEMICAL CARCINOGENESIS

National Institutes of Health

Grant: 1P40OD010440-01

Caenorhabditis Genetics Center

National Institutes of Health

Grant: 5R01GM121625-03

Novel signals regulate cell fate patterning

FWCI

0.00

Citation Percentile

0.1%

greenLicense: CC BY

repositoryhttps://doi.org/10.17615/qf66-d592

https://doi.org/10.1093/g3journal/jkab234

https://academic.oup.com/g3journal/article-pdf/11/9/jkab234/40519425/jkab234.pdf

https://dx.doi.org/10.17615/qf66-d592

https://pubmed.ncbi.nlm.nih.gov/34544135

Fields of Study

Fault Detection and Control SystemsMachine Learning and Data ClassificationAdvanced Control Systems Optimization0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Selection (genetic algorithm)Computer scienceArtificial intelligenceInvestigationGeneticsAnimalsQH426-470Caenorhabditis elegansCaenorhabditis elegans Proteins