ProTrack: An Interactive Multi-Omics Data Browser for Proteogenomic Studies

被引：11

作者：

Calinawan, Anna Pamela ^{[1
]}

Song, Xiaoyu ^{[2
,3
]}

Ji, Jiayi ^{[2
,3
]}

Dhanasekaran, Saravana Mohan ^{[4
]}

Petralia, Francesca ^{[1
]}

Wang, Pei ^{[1
]}

Reva, Boris ^{[1
]}

机构：

[1] Icahn Sch Med Mt Sinai, Dept Genet & Genom Sci, New York, NY 10029 USA

[2] Icahn Sch Med Mt Sinai, Dept Populat Hlth Sci & Policy, New York, NY 10029 USA

[3] Icahn Sch Med Mt Sinai, Tisch Canc Inst, New York, NY 10029 USA

[4] Univ Michigan, Dept Pathol, Ann Arbor, MI 48109 USA

来源：

PROTEOMICS | 2020年 / 20卷 / 21-22期

关键词：

D O I：

10.1002/pmic.201900359

中图分类号：

Q5 [生物化学];

学科分类号：

071010 ; 081704 ;

摘要：

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) initiative has generated extensive multi-omics data resources of deep proteogenomic profiles for multiple cancer types. To enable the broader community of biological and medical researchers to intuitively query, explore, and download data and analysis results from various CPTAC projects, a prototype user-friendly web application called "ProTrack" is built with the CPTAC clear cell renal cell carcinoma (ccRCC) data set (). Here the salient features of this application which provides a dynamic, comprehensive, and granular visualization of the rich proteogenomic data is described.

引用

页数：5

共 50 条

[21] Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets
Argelaguet, Ricard
Velten, Britta
Arnol, Damien
Dietrich, Sascha
Zenz, Thorsten
Marioni, John C.
Buettner, Florian
Huber, Wolfgang
Stegle, Oliver
MOLECULAR SYSTEMS BIOLOGY, 2018, 14 (06)
[22] MODAS: exploring maize germplasm with multi-omics data association studies
Liu, Songyu
Xu, Feng
Xu, Yuetong
Wang, Qian
Yan, Jun
Wang, Jinyu
Wang, Xianbing
Wang, Xiangfeng
SCIENCE BULLETIN, 2022, 67 (09) : 903 - 906
[23] Panomicon: A web-based environment for interactive, visual analysis of multi-omics data
Osorio, Rodolfo S. Allendes
Nystrom-Persson, Johan T.
Nojima, Yosui
Kosugi, Yuji
Mizuguchi, Kenji
Natsume-Kitatani, Yayoi
HELIYON, 2020, 6 (08)
[24] ExpressVis: a biologist-oriented interactive web server for exploring multi-omics data
Liu, Xian
Xu, Kaikun
Tao, Xin
Yin, Ronghua
Ren, Guangming
Yu, Miao
Li, Changyan
Chen, Hui
Zhao, Ke
Xiang, Shensi
Gao, Huiying
Bo, Xiaochen
Chang, Cheng
Yang, Xiaoming
NUCLEIC ACIDS RESEARCH, 2022, 50 (W1) : W312 - W321
[25] Proteogenomic signatures of Osteoporotic Fractures and Risk Prediction: A multi-omics approach for musculoskeletal biology
Hsu, Yi-Hsiang
Chang, Yu-Tien
Yu, Fangtang
Reppe, Sjur
Gautvik, Kaare
JOURNAL OF BONE AND MINERAL RESEARCH, 2024, 39 : 277 - 277
[26] Progress of bioinformatics studies for multi-omics and multi- modal data in complex diseases
Liu, Xiaofan
Lu, Zhi John
CHINESE SCIENCE BULLETIN-CHINESE, 2024, 69 (30): : 4432 - 4446
[27] Multi-omics Visualization Platform: An extensible Galaxy plug-in for multi-omics data visualization and exploration
McGowan, Thomas
Johnson, James E.
Kumar, Praveen
Sajulga, Ray
Mehta, Subina
Jagtap, Pratik D.
Griffin, Timothy J.
GIGASCIENCE, 2020, 9 (04):
[28] Multi-omics approach to stem cell studies
Singh, Himadri
MINERVA BIOTECNOLOGICA, 2017, 29 (04) : 169 - 173
[29] Multi-Omics Approaches in Genetic Epidemiology Studies
Kechris, Katerina
GENETIC EPIDEMIOLOGY, 2017, 41 (07) : 644 - 644
[30] Making multi-omics data accessible to researchers
Ana Conesa
Stephan Beck
Scientific Data, 6

← 1 2 3 4 5 →