Data integration

Data integration is the process of combining data generated using a variety of different research methods in order to enable detection of underlying themes and, in computational biology and bioinformatics, biological principles. Data integration is important in biology owing to the large and different 'omics' datasets now available.

Latest Research and Reviews

News and Comment

  • Comments and Opinion
    | Open Access

    Efficient response to the pandemic through the mobilization of the larger scientific community is challenged by the limited reusability of the available primary genomic data. Here, the Genomic Standards Consortium board highlights the essential need for contextual genomic data FAIRness, for empowering key data-driven biological questions.

    • Lynn M. Schriml
    • , Maria Chuvochina
    • , Neil Davies
    • , Emiley A. Eloe-Fadrosh
    • , Robert D. Finn
    • , Philip Hugenholtz
    • , Christopher I. Hunter
    • , Bonnie L. Hurwitz
    • , Nikos C. Kyrpides
    • , Folker Meyer
    • , Ilene Karsch Mizrachi
    • , Susanna-Assunta Sansone
    • , Granger Sutton
    • , Scott Tighe
    •  & Ramona Walls
  • Comments and Opinion |

    Single-cell omics approaches provide high-resolution data on cellular phenotypes, developmental dynamics and communication networks in diverse tissues and conditions. Emerging technologies now measure different modalities of individual cells, such as genomes, epigenomes, transcriptomes and proteomes, in addition to spatial profiling. Combined with analytical approaches, these data open new avenues for accurate reconstruction of gene-regulatory and signaling networks driving cellular identity and function. Here we summarize computational methods for analysis and integration of single-cell omics data across different modalities and discuss their applications, challenges and future directions.

    • Mirjana Efremova
    •  & Sarah A. Teichmann
    Nature Methods 17, 14-17
  • Comments and Opinion
    | Open Access

    A special collection on multi-omics data sharing, launched today at Scientific Data, offers to the scientific community a compendium of multi-omics datasets ready for reuse, which showcase the diversity of multi-omics projects and highlights innovative approaches for preprocessing, quality control, hosting and access.

    • Ana Conesa
    •  & Stephan Beck