Evidence map›Paper›PMID 34136100›Full record

ReviewComputational and structural biotechnology journal2021

Making fundamental scientific discoveries by combining information from literature, databases, and computational tools - An example.

Bastian Stielow, Clara Simon, Robert Liefke

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2021. 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.

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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

3 authors.

Bastian StielowInstitute of Molecular Biology and Tumor Research (IMT), Philipps University of Marburg, 35043 Marburg, Germany.
Clara SimonInstitute of Molecular Biology and Tumor Research (IMT), Philipps University of Marburg, 35043 Marburg, Germany.
Robert LiefkeInstitute of Molecular Biology and Tumor Research (IMT), Philipps University of Marburg, 35043 Marburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the amount of available literature, data and computational tools has increased exponentially, providing opportunities and challenges to make use of this vast amount of material. Here, we describe how we utilized publicly available information to identify the previously hardly characterized protein SAMD1 (SAM domain-containing protein 1) as a novel unmethylated CpG island-binding protein. This discovery is an example, how the richness of material and tools on the internet can be used to make scientific breakthroughs, but also the hurdles that may occur. Specifically, we discuss how the misrepresentation of SAMD1 in literature and databases may have prevented an earlier characterization of this protein and we address what can be learned from this example.

Indexed as

CpG islandsDatabasesHuman genomeProtein structure predictionSAMD1Transcription factors

Identifiers

PMID34136100
PMCPMC8175269

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.