文献
J-GLOBAL ID:202002272429270135
整理番号:20A0901181
癌不均一性を解剖するための経路知識を活用したGauss混合モデル【JST・京大機械翻訳】
A Gaussian Mixture-Model Exploiting Pathway Knowledge for Dissecting Cancer Heterogeneity
著者 (6件):
Kapoor Rajan
(Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA)
,
Datta Aniruddha
(Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USA)
,
Sima Chao
(Center for Bioinformatics and Genomic Systems Engineering, TEES/Texas A&M University, College Station, TX, USA)
,
Hua Jianping
(Center for Bioinformatics and Genomic Systems Engineering, TEES/Texas A&M University, College Station, TX, USA)
,
Lopes Rosana
(Center for Bioinformatics and Genomic Systems Engineering, TEES/Texas A&M University, College Station, TX, USA)
,
Bittner Michael L.
(Translational Genomics Research Institute, Phoenix, AZ, USA)
資料名:
IEEE/ACM Transactions on Computational Biology and Bioinformatics
(IEEE/ACM Transactions on Computational Biology and Bioinformatics)
巻:
17
号:
2
ページ:
459-468
発行年:
2020年
JST資料番号:
W1409A
ISSN:
1545-5963
CODEN:
ITCBCY
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)