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Unsupervised Machine Learning Algorithms to Characterize Single-Cell Heterogeneity and Perturbation Response
Unsupervised Machine Learning Algorithms to Characterize Single-Cell Heterogeneity and Per...
Unsupervised Machine Learning Algorithms to Characterize Single-Cell Heterogeneity and Perturbation Response

Detailed Information

자료유형  
 학위논문파일 국외
ISBN  
9798522999056
DDC  
575
저자명  
Burkhardt, Daniel Bernard.
서명/저자  
Unsupervised Machine Learning Algorithms to Characterize Single-Cell Heterogeneity and Perturbation Response
발행사항  
[Sl] : Yale University, 2021
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2021
형태사항  
164 p
주기사항  
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
주기사항  
Advisor: Krishnaswamy, Smita.
학위논문주기  
Thesis (Ph.D.)--Yale University, 2021.
사용제한주기  
This item must not be sold to any third party vendors.
일반주제명  
Genetics
일반주제명  
Biology
일반주제명  
Computer science
일반주제명  
Artificial intelligence
일반주제명  
Deep learning
일반주제명  
Datasets
일반주제명  
Signal processing
일반주제명  
Data analysis
일반주제명  
Noise
일반주제명  
Clustering
일반주제명  
Genes
일반주제명  
Mutagenesis
일반주제명  
Visualization
일반주제명  
Neurons
일반주제명  
Principal components analysis
일반주제명  
Fibroblasts
일반주제명  
Graph representations
일반주제명  
Neural networks
일반주제명  
Quantitative analysis
일반주제명  
Methods
일반주제명  
Algorithms
일반주제명  
Geometry
키워드  
Computational biology
키워드  
Genomics
키워드  
Graph signal processing
키워드  
Machine learning
키워드  
Manifold
키워드  
Single-cell heterogeniety
기타저자  
Yale University Genetics
기본자료저록  
Dissertations Abstracts International. 83-02B.
기본자료저록  
Dissertation Abstract International
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■035    ▼a(MiAaPQ)AAI28322261
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a575
■1001  ▼aBurkhardt,  Daniel  Bernard.
■24510▼aUnsupervised  Machine  Learning  Algorithms  to  Characterize  Single-Cell  Heterogeneity  and  Perturbation  Response
■260    ▼a[Sl]▼bYale  University▼c2021
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2021
■300    ▼a164  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  83-02,  Section:  B.
■500    ▼aAdvisor:  Krishnaswamy,  Smita.
■5021  ▼aThesis  (Ph.D.)--Yale  University,  2021.
■506    ▼aThis  item  must  not  be  sold  to  any  third  party  vendors.
■590    ▼aSchool  code:  0265.
■650  4▼aGenetics
■650  4▼aBiology
■650  4▼aComputer  science
■650  4▼aArtificial  intelligence
■650  4▼aDeep  learning
■650  4▼aDatasets
■650  4▼aSignal  processing
■650  4▼aData  analysis
■650  4▼aNoise
■650  4▼aClustering
■650  4▼aGenes
■650  4▼aMutagenesis
■650  4▼aVisualization
■650  4▼aNeurons
■650  4▼aPrincipal  components  analysis
■650  4▼aFibroblasts
■650  4▼aGraph  representations
■650  4▼aNeural  networks
■650  4▼aQuantitative  analysis
■650  4▼aMethods
■650  4▼aAlgorithms
■650  4▼aGeometry
■653    ▼aComputational  biology
■653    ▼aGenomics
■653    ▼aGraph  signal  processing
■653    ▼aMachine  learning
■653    ▼aManifold
■653    ▼aSingle-cell  heterogeniety
■690    ▼a0369
■690    ▼a0984
■690    ▼a0800
■690    ▼a0306
■71020▼aYale  University▼bGenetics.
■7730  ▼tDissertations  Abstracts  International▼g83-02B.
■773    ▼tDissertation  Abstract  International
■790    ▼a0265
■791    ▼aPh.D.
■792    ▼a2021
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16051413▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.
■980    ▼a202202▼f2022

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