| LDR | | 00000nmm u2200205 4500 |
| 001 | | 000000331083 |
| 005 | | 20241108141602 |
| 008 | | 181129s2018 ||| | | | eng d |
| 020 | |
▼a 9780438261792 |
| 035 | |
▼a (MiAaPQ)AAI10837508 |
| 035 | |
▼a (MiAaPQ)cumc.columbia:10044 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 049 | 1 |
▼f DP |
| 082 | 0 |
▼a 574 |
| 100 | 1 |
▼a Drill, Esther. |
| 245 | 10 |
▼a Statistical Methods for Integrated Cancer Genomic Data Using a Joint Latent Variable Model. |
| 260 | |
▼a [S.l.] :
▼b Columbia University.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 116 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Advisers: Yuanjia Wang |
| 502 | 1 |
▼a Thesis (Dr.P.H.)--Columbia University, 2018. |
| 520 | |
▼a Inspired by the TCGA (The Cancer Genome Atlas), we explore multimodal genomic datasets with integrative methods using a joint latent variable approach. We use iCluster+, an existing clustering method for integrative data, to identify potential s |
| 590 | |
▼a School code: 0054. |
| 650 | 4 |
▼a Biostatistics. |
| 650 | 4 |
▼a Statistics. |
| 690 | |
▼a 0308 |
| 690 | |
▼a 0463 |
| 710 | 20 |
▼a Columbia University.
▼b Biostatistics. |
| 773 | 0 |
▼t Dissertation Abstracts International
▼g 79-12B(E). |
| 773 | |
▼t Dissertation Abstract International |
| 790 | |
▼a 0054 |
| 791 | |
▼a Dr.P.H. |
| 792 | |
▼a 2018 |
| 793 | |
▼a English |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999563
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자
▼b 관리자 |