A state space representation of VAR models with sparse learning for dynamic gene networks.

Genome informatics. International Conference on Genome Informatics

Volumn 22, Issue , 2010, Pages 56-68

  Kojima, Kaname ^a   Yamaguchi, Rui ^b   Imoto, Seiya ^b   Yamauchi, Mai ^b   Nagasaki, Masao ^b   Yoshida, Ryo ^b   Shimamura, Teppei ^b   Ueno, Kazuko ^b   Higuchi, Tomoyuki ^b   Gotoh, Noriko ^b   Miyano, Satoru ^b  

^a UNIVERSITY OF TOKYO   (Japan)

^b NONE

Author keywords

[No Author keywords available]

Indexed keywords

EGFR PROTEIN, HUMAN; EPIDERMAL GROWTH FACTOR RECEPTOR; GEFITINIB; PROTEIN KINASE INHIBITOR; QUINAZOLINE DERIVATIVE; TUMOR PROTEIN;

ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BIOLOGY; CELL CULTURE; DRUG ANTAGONISM; DRUG EFFECT; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORK; GENETICS; HUMAN; LUNG; LUNG TUMOR; METABOLISM; PROBABILITY; REGRESSION ANALYSIS; STATISTICAL MODEL; TIME;

CELLS, CULTURED; COMPUTATIONAL BIOLOGY; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; HUMANS; LUNG; LUNG NEOPLASMS; MODELS, BIOLOGICAL; MODELS, STATISTICAL; NEOPLASM PROTEINS; PATTERN RECOGNITION, AUTOMATED; PROBABILITY; PROTEIN KINASE INHIBITORS; QUINAZOLINES; RECEPTOR, EPIDERMAL GROWTH FACTOR; REGRESSION ANALYSIS; TIME FACTORS;

MLCS; MLOWN;

EID: 77954653646     PISSN: 09199454     EISSN: None     Source Type: Journal    
DOI: 10.1142/9781848165786_0006     Document Type: Article

References (0)