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
  • [1] MOOMIN - Mathematical explOration of 'Omics data on a MetabolIc Network
    Pusa, Taneli
    Ferrarini, Mariana Galvao
    Andrade, Ricardo
    Mary, Arnaud
    Marchetti-Spaccamela, Alberto
    Stougie, Leen
    Sagot, Marie-France
    BIOINFORMATICS, 2020, 36 (02) : 514 - 523
  • [2] Integrative Analysis of Cancer Omics Data for Prognosis Modeling
    Wang, Shuaichao
    Wu, Mengyun
    Ma, Shuangge
    GENES, 2019, 10 (08)
  • [3] Integrating Omics Data in Genome-Scale Metabolic Modeling: A Methodological Perspective for Precision Medicine
    Sen, Partho
    Oresic, Matej
    METABOLITES, 2023, 13 (07)
  • [4] Reconstruction of genome-scale human metabolic models using omics data
    Ryu, Jae Yong
    Kim, Hyun Uk
    Lee, Sang Yup
    INTEGRATIVE BIOLOGY, 2015, 7 (08) : 859 - 868
  • [5] Obesity, metabolic health and omics: Current status and future directions
    Paczkowska-Abdulsalam, Magdalena
    Kretowski, Adam
    WORLD JOURNAL OF DIABETES, 2021, 12 (04) : 420 - 436
  • [6] Network modeling of single-cell omics data: challenges, opportunities, and progresses
    Blencowe, Montgomery
    Arneson, Douglas
    Ding, Jessica
    Chen, Yen-Wei
    Saleem, Zara
    Yang, Xia
    EMERGING TOPICS IN LIFE SCIENCES, 2019, 3 (04) : 379 - 398
  • [7] Principles and challenges of modeling temporal and spatial omics data
    Velten, Britta
    Stegle, Oliver
    NATURE METHODS, 2023, 20 (10) : 1462 - 1474
  • [8] SOTIP is a versatile method for microenvironment modeling with spatial omics data
    Yuan, Zhiyuan
    Li, Yisi
    Shi, Minglei
    Yang, Fan
    Gao, Juntao
    Yao, Jianhua
    Zhang, Michael Q.
    NATURE COMMUNICATIONS, 2022, 13 (01)
  • [9] Computational solutions for omics data
    Berger, Bonnie
    Peng, Jian
    Singh, Mona
    NATURE REVIEWS GENETICS, 2013, 14 (05) : 333 - 346
  • [10] Transcriptional and metabolic data integration and modeling for identification of active pathways
    Jauhiainen, Alexandra
    Nerman, Olle
    Michailidis, George
    Jornsten, Rebecka
    BIOSTATISTICS, 2012, 13 (04) : 748 - 761