Evidence map›Paper›PMID 27480368›Full record

ArticleSocial science research2016

Opportunities and challenges of big data for the social sciences: The case of genomic data.

Hexuan Liu, Guang Guo

Abstract read
In one paragraph

Article in Social science research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Exome sequencing of UK birth cohorts.Wellcome open research · 2024
    Article
  2. Efficient Federated Kinship Relationship Identification.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    Article
  3. Article
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  5. Article
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  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hexuan LiuDepartment of Sociology, The University of North Carolina at Chapel Hill, USA; Carolina Population Center, The University of North Carolina at Chapel Hill, USA; School of Criminal Justice, The University of Cincinnati, USA. Electronic address: hexuanl@live.unc.edu.
Guang GuoDepartment of Sociology, The University of North Carolina at Chapel Hill, USA; Carolina Center for Genome Sciences, The University of North Carolina at Chapel Hill, USA; Carolina Population Center, The University of North Carolina at Chapel Hill, USA.

Funding

Carolina Population CenterR24HD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI MORGAN, SAMUEL PHILIP · 2005 to 2014
$10.0M
Research Services CoreP2CHD050924 · NICHD · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KAREN B GUZZO · 2015 to 2026
$9.6M
NICHD NIH HHS P2C HD050924NICHD NIH HHS R24 HD050924
6 · The paper itself

Abstract

In this paper, we draw attention to one unique and valuable source of big data, genomic data, by demonstrating the opportunities they provide to social scientists. We discuss different types of large-scale genomic data and recent advances in statistical methods and computational infrastructure used to address challenges in managing and analyzing such data. We highlight how these data and methods can be used to benefit social science research.

Indexed as

GenomicsSocial SciencesComputational BiologyGenomeHumansResearchGene-environment interactionGenomic data

Identifiers

PMID27480368
PMCPMC5480284

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.