Omics data input for metabolic modeling

被引:37
作者
Rai, Amit [1 ]
Saito, Kazuki [1 ,2 ]
机构
[1] Chiba Univ, Grad Sch Pharmaceut Sci, Chuo Ku, 1-8-1 Inohana, Chiba 2608675, Japan
[2] RIKEN Ctr Sustainable Resource Sci, Tsurumi Ku, 1-7-22 Suehiro Cho, Yokohama, Kanagawa 2300045, Japan
关键词
C-13 FLUX ANALYSIS; NETWORK RECONSTRUCTION; FUNCTIONAL ANNOTATION; RNA-SEQ; ARABIDOPSIS; GENOMICS; INTEGRATION; EXPRESSION; PROTEOMICS; PATHWAYS;
D O I
10.1016/j.copbio.2015.10.010
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.
引用
收藏
页码:127 / 134
页数:8
相关论文
共 50 条
  • [21] OmixLitMiner: A Bioinformatics Tool for Prioritizing Biological Leads from 'Omics Data Using Literature Retrieval and Data Mining
    Steffen, Pascal
    Wu, Jemma
    Hariharan, Shubhang
    Voss, Hannah
    Raghunath, Vijay
    Molloy, Mark P.
    Schlueter, Hartrnut
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2020, 21 (04)
  • [22] An advanced systems biology framework of feature engineering for cold tolerance genes discovery from integrated omics and non-omics data in soybean
    Kao, Pei-Hsiu
    Baiya, Supaporn
    Lai, Zheng-Yuan
    Huang, Chih-Min
    Jhan, Li-Hsin
    Lin, Chian-Jiun
    Lai, Ya-Syuan
    Kao, Chung-Feng
    FRONTIERS IN PLANT SCIENCE, 2022, 13
  • [23] "Omics" data and levels of evidence for biomarker discovery
    Ghosh, Debashis
    Poisson, Laila M.
    GENOMICS, 2009, 93 (01) : 13 - 16
  • [24] 'Omics Data Sharing
    Field, Dawn
    Sansone, Susanna-Assunta
    Collis, Amanda
    Booth, Tim
    Dukes, Peter
    Gregurick, Susan K.
    Kennedy, Karen
    Kolar, Patrik
    Kolker, Eugene
    Maxon, Mary
    Millard, Sian
    Mugabushaka, Alexis-Michel
    Perrin, Nicola
    Remacle, Jacques E.
    Remington, Karin
    Rocca-Serra, Philippe
    Taylor, Chris F.
    Thorley, Mark
    Tiwari, Bela
    Wilbanks, John
    SCIENCE, 2009, 326 (5950) : 234 - 236
  • [25] Integrative modeling of multi-omics data to identify cancer drivers and infer patient-specific gene activity
    Pavel, Ana B.
    Sonkin, Dmitriy
    Reddy, Anupama
    BMC SYSTEMS BIOLOGY, 2016, 10
  • [26] Transforming omics data into context: Bioinformatics on genomics and proteomics raw data
    Perco, Paul
    Rapberger, Ronald
    Siehs, Christian
    Lukas, Arno
    Oberbauer, Rainer
    Mayer, Gert
    Mayer, Bernd
    ELECTROPHORESIS, 2006, 27 (13) : 2659 - 2675
  • [27] Challenges in the Integration of Omics and Non-Omics Data
    Lopez de Maturana, Evangelina
    Alonso, Lola
    Alarcon, Pablo
    Adoracion Martin-Antoniano, Isabel
    Pineda, Silvia
    Piorno, Lucas
    Luz Calle, M.
    Malats, Nuria
    GENES, 2019, 10 (03)
  • [28] Advantages of omics approaches for elucidating metabolic changes in diabetic peripheral neuropathy
    Yako, Hideji
    Niimi, Naoko
    Takaku, Shizuka
    Sango, Kazunori
    FRONTIERS IN ENDOCRINOLOGY, 2023, 14
  • [29] Multi-Omics Data Analysis Uncovers Molecular Networks and Gene Regulators for Metabolic Biomarkers
    Jung, Su Yon
    BIOMOLECULES, 2021, 11 (03) : 1 - 13
  • [30] Characterizing the Metabolic and Immune Landscape of Non-small Cell Lung Cancer Reveals Prognostic Biomarkers Through Omics Data Integration
    Wang, Fengjiao
    Zhang, Yuanfu
    Hao, Yangyang
    Li, Xuexin
    Qi, Yue
    Xin, Mengyu
    Xiao, Qifan
    Wang, Peng
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2021, 9