Learning Gene Networks under SNP Perturbations Using eQTL Datasets

PLoS Computational Biology

Volumn 10, Issue 2, 2014, Pages

  Zhang, Lingxue ^a   Kim, Seyoung ^a  

^a Carnegie Mellon University ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECODING; GENE EXPRESSION; GRAPHIC METHODS; LEARNING ALGORITHMS; PERTURBATION TECHNIQUES; YEAST;

DIFFERENTIAL GENE EXPRESSIONS; GENE INTERACTIONS; GENE NETWORKS; GENETICAL GENOMICS; GENOME-WIDE PROFILING; GENOMICS ANALYSIS; KNOCK OUTS; QUANTITATIVE TRAIT LOCUS; REGULATORY SYSTEMS; STATISTIC MODELING;

POPULATION STATISTICS;

DATA ANALYSIS; DNA REPLICATION; EXPERIMENTAL MODEL; GENE EXPRESSION; GENETIC MODEL; GENOMICS; HAPLOTYPE MAP; LEARNING; LEARNING ALGORITHM; MODEL; QUANTITATIVE TRAIT LOCUS; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS; STATISTICAL MODEL; STRESS; YEAST; ALGORITHM; ARTIFICIAL INTELLIGENCE; BIOLOGICAL MODEL; BIOLOGY; COMPUTER SIMULATION; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HUMAN; NUCLEIC ACID DATABASE; SACCHAROMYCES CEREVISIAE;

FUNGAL DNA;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL BIOLOGY; COMPUTER SIMULATION; DATABASES, NUCLEIC ACID; DNA, FUNGAL; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; LINEAR MODELS; MODELS, GENETIC; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE; QUANTITATIVE TRAIT LOCI; SACCHAROMYCES CEREVISIAE;

EID: 84901313606     PISSN: 1553734X     EISSN: 15537358     Source Type: Journal    
DOI: 10.1371/journal.pcbi.1003420     Document Type: Article

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