Evidence map›Paper›PMID 30839275›Full record

ArticleeLife2019

Data science for the scientific life cycle.

Daphne Ezer, Kirstie Whitaker

Abstract read
In one paragraph

Article in eLife, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Optimal linear ensemble of binary classifiers.Bioinformatics advances · 2024
    Article
  3. Article
  4. Article
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.

Daphne Ezer *Alan Turing Institute, London, United Kingdom.ORCID 0000-0002-1685-6909
Kirstie Whitaker *Alan Turing Institute, London, United Kingdom.ORCID 0000-0001-8498-4059

Funding

REGULATION OF MACROPHAGE FUNCTION BY INTERLEUKIN-2K08CA001360 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ECONOMOU, JAMES S. · 1988 to 1990
–
Alan Turing Institute TU/A/000017Engineering and Physical Sciences Research Council EP/S001360/1
6 · The paper itself

Abstract

Data science can be incorporated into every stage of a scientific study. Here we describe how data science can be used to generate hypotheses, to design experiments, to perform experiments, and to analyse data. We also present our vision for how data science techniques will be an integral part of the laboratory of the future.

Indexed as

Biomedical ResearchComputational BiologyData Sciencecomputational biologydata scienceexperimental designnoneopen sciencereproducibilitysystems biology

Identifiers

PMID30839275
PMCPMC6402833

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.