Data integration

Definition

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

  • Research Highlights |

    A new computational method integrates RNA single-cell sequencing and spatial data.

    • Tal Nawy
  • News and Views |

    The surge in single-cell and single-nucleus RNA-sequencing has raised the question of the value of bulk tissue transcriptomics. Kelley et al. describe an analysis framework by which existing bulk transcriptomic data can be reanalyzed using cell-type-specific data to yield insights into cell-type variation across brain regions and diseases.

    • Vilas Menon
    Nature Neuroscience 21, 1142–1144
  • Comments and Opinion |

    Biomedical ‘big data’ has opened opportunities for data repurposing to reveal new insights into complex diseases. Public data on IBD have been repurposed for novel diagnostics and therapeutics, and these datasets continue to grow. Here, we discuss the practicalities and implications of open data informatics for IBD.

    • Vivek A. Rudrapatna
    •  & Atul J. Butte
  • Comments and Opinion | | open

    • Adam P Arkin
    • , Robert W Cottingham
    • , Christopher S Henry
    • , Nomi L Harris
    • , Rick L Stevens
    • , Sergei Maslov
    • , Paramvir Dehal
    • , Doreen Ware
    • , Fernando Perez
    • , Shane Canon
    • , Michael W Sneddon
    • , Matthew L Henderson
    • , William J Riehl
    • , Dan Murphy-Olson
    • , Stephen Y Chan
    • , Roy T Kamimura
    • , Sunita Kumari
    • , Meghan M Drake
    • , Thomas S Brettin
    • , Elizabeth M Glass
    • , Dylan Chivian
    • , Dan Gunter
    • , David J Weston
    • , Benjamin H Allen
    • , Jason Baumohl
    • , Aaron A Best
    • , Ben Bowen
    • , Steven E Brenner
    • , Christopher C Bun
    • , John-Marc Chandonia
    • , Jer-Ming Chia
    • , Ric Colasanti
    • , Neal Conrad
    • , James J Davis
    • , Brian H Davison
    • , Matthew DeJongh
    • , Scott Devoid
    • , Emily Dietrich
    • , Inna Dubchak
    • , Janaka N Edirisinghe
    • , Gang Fang
    • , José P Faria
    • , Paul M Frybarger
    • , Wolfgang Gerlach
    • , Mark Gerstein
    • , Annette Greiner
    • , James Gurtowski
    • , Holly L Haun
    • , Fei He
    • , Rashmi Jain
    • , Marcin P Joachimiak
    • , Kevin P Keegan
    • , Shinnosuke Kondo
    • , Vivek Kumar
    • , Miriam L Land
    • , Folker Meyer
    • , Marissa Mills
    • , Pavel S Novichkov
    • , Taeyun Oh
    • , Gary J Olsen
    • , Robert Olson
    • , Bruce Parrello
    • , Shiran Pasternak
    • , Erik Pearson
    • , Sarah S Poon
    • , Gavin A Price
    • , Srividya Ramakrishnan
    • , Priya Ranjan
    • , Pamela C Ronald
    • , Michael C Schatz
    • , Samuel M D Seaver
    • , Maulik Shukla
    • , Roman A Sutormin
    • , Mustafa H Syed
    • , James Thomason
    • , Nathan L Tintle
    • , Daifeng Wang
    • , Fangfang Xia
    • , Hyunseung Yoo
    • , Shinjae Yoo
    •  & Dantong Yu
    Nature Biotechnology 36, 566–569