Towards multi-omics synthetic data integration

被引：0
|
作者：
Selvarajoo, Kumar [1 ,2 ,3 ]
Maurer-Stroh, Sebastian [1 ,2 ]
机构：
[1] ASTAR, Biomol Sequence Funct Div, BII, Singapore 138671, Singapore
[2] NUS, Yong Loo Lin Sch Med, Synthet Biol Translat Res Program, Singapore 117456, Singapore
[3] Nanyang Technol Univ NTU, Sch Biol Sci, Singapore 639798, Singapore
来源：
BRIEFINGS IN BIOINFORMATICS | 2024年 / 25卷 / 03期
关键词：
synthetic data; process-driven; data-driven; machine learning; multi-omics;
D O I：
10.1093/bib/bbae213
中图分类号：
Q5 [生物化学];
学科分类号：
071010 ; 081704 ;
摘要：
Across many scientific disciplines, the development of computational models and algorithms for generating artificial or synthetic data is gaining momentum. In biology, there is a great opportunity to explore this further as more and more big data at multi-omics level are generated recently. In this opinion, we discuss the latest trends in biological applications based on process-driven and data-driven aspects. Moving ahead, we believe these methodologies can help shape novel multi-omics-scale cellular inferences.
引用
收藏
页数：3
相关论文
共 50 条
  • [1] Survey on Multi-omics, and Multi-omics Data Analysis, Integration and Application
    Shahrajabian, Mohamad Hesam
    Sun, Wenli
    CURRENT PHARMACEUTICAL ANALYSIS, 2023, 19 (04) : 267 - 281
  • [2] A cloud solution for multi-omics data integration
    Tordini, Fabio
    2016 INT IEEE CONFERENCES ON UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTING, SCALABLE COMPUTING AND COMMUNICATIONS, CLOUD AND BIG DATA COMPUTING, INTERNET OF PEOPLE, AND SMART WORLD CONGRESS (UIC/ATC/SCALCOM/CBDCOM/IOP/SMARTWORLD), 2016, : 559 - 566
  • [3] The human microbiome and genetic disease: towards the integration of metagenomic and multi-omics data
    Huiying Zhao
    Human Genetics, 2021, 140 : 701 - 702
  • [4] The human microbiome and genetic disease: towards the integration of metagenomic and multi-omics data
    Zhao, Huiying
    HUMAN GENETICS, 2021, 140 (05) : 701 - 702
  • [5] Integration of solutions and services for multi-omics data analysis towards personalized medicine
    Reska, Daniel
    Czajkowski, Marcin
    Jurczuk, Krzysztof
    Boldak, Cezary
    Kwedlo, Wojciech
    Bauer, Witold
    Koszelew, Jolanta
    Kretowski, Marek
    BIOCYBERNETICS AND BIOMEDICAL ENGINEERING, 2021, 41 (04) : 1646 - 1663
  • [6] 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)
  • [7] Multi-omics data integration by generative adversarial network
    Ahmed, Khandakar Tanvir
    Sun, Jiao
    Cheng, Sze
    Yong, Jeongsik
    Zhang, Wei
    BIOINFORMATICS, 2022, 38 (01) : 179 - 186
  • [8] Prospects and challenges of multi-omics data integration in toxicology
    Sebastian Canzler
    Jana Schor
    Wibke Busch
    Kristin Schubert
    Ulrike E. Rolle-Kampczyk
    Hervé Seitz
    Hennicke Kamp
    Martin von Bergen
    Roland Buesen
    Jörg Hackermüller
    Archives of Toxicology, 2020, 94 : 371 - 388
  • [9] A survey on data integration for multi-omics sample clustering
    Lovino, Marta
    Randazzo, Vincenzo
    Ciravegna, Gabriele
    Barbiero, Pietro
    Ficarra, Elisa
    Cirrincione, Giansalvo
    NEUROCOMPUTING, 2022, 488 : 494 - 508
  • [10] Multi-omics data integration approaches for precision oncology
    Correa-Aguila, Raidel
    Alonso-Pupo, Niuxia
    Hernandez-Rodriguez, Erix W.
    MOLECULAR OMICS, 2022, 18 (06) : 469 - 479
12345