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Article . 2024
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Briefings in Bioinformatics
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Towards multi-omics synthetic data integration

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 27 Mar 2024 Singapore English Publisher:Oxford University Press (OUP)Journal:Briefings in Bioinformatics, volume 25 (issn: 1467-5463, eissn: 1477-4054, Copyright policy )
Authors: Kumar Selvarajoo; Sebastian Maurer-Stroh;

doi: 10.1093/bib/bbae213

pmid: 38711370

pmc: PMC11074586

handle: 10356/180054

Towards multi-omics synthetic data integration

Abstract

Abstract 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.

Country
Singapore
Related Organizations
Keywords

Big Data, Proteomics, Multi-omics, Synthetic data, Computational Biology, Genomics, Opinion Article, Multiomics, 004, Health and Life Sciences, Medicine, Humans, Algorithms

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    		 Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    		 Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    		 Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
gold