Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome

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Self-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome is …
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P819ADS bibcode2015PLoSO..1029126H
P356DOI10.1371/JOURNAL.PONE.0129126
P932PMC publication ID4482027
P698PubMed publication ID26111164
P5875ResearchGate publication ID279302994

P2093author name stringKrzysztof J Cios
Katheleen J Gardiner
Clara Higuera
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Molecular responses of the Ts65Dn and Ts1Cje mouse models of Down syndrome to MK-801.Q37179196
Protein profiles associated with context fear conditioning and their modulation by memantineQ37687443
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P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue6
P407language of work or nameEnglishQ1860
P921main subjectDown syndromeQ47715
self-organizationQ609408
P304page(s)e0129126
P577publication date2015-01-01
P1433published inPLOS OneQ564954
P1476titleSelf-Organizing Feature Maps Identify Proteins Critical to Learning in a Mouse Model of Down Syndrome
P478volume10

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cites work (P2860)
Q97541344A comprehensive empirical comparison of hubness reduction in high-dimensional spaces
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Q59336769Bi-stream CNN Down Syndrome screening model based on genotyping array
Q64287672Combining self-organizing maps and biplot analysis to preselect maize phenotypic components based on UAV high-throughput phenotyping platform
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Q61808535In silico identification of critical proteins associated with learning process and immune system for Down syndrome
Q38603122Robust continuous clustering.
Q42314998Use of self-organizing maps for analyzing the behavior of canines displaced towards midline under interceptive treatment
Q48677943WITHDRAWN: Benchmarking swarm intelligence clustering algorithms with case study of medical data

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