Evidence map›Paper›PMID 22772728›Full record

ArticleNature methods2012

Identification of cross-linked peptides from complex samples.

Bing Yang, Yan-Jie Wu, Ming Zhu, Sheng-Bo Fan, Jinzhong Lin, Kun Zhang, Shuang Li, Hao Chi, Yu-Xin Li, Hai-Feng Chen and 9 more

Abstract read
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In one paragraph

Article in Nature methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 348 papers.

0numbers the graph read from it
0cells of the map it votes in
348citing 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

348 citing papers in PubMed.

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288 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Bing YangCollege of Biological Sciences, China Agricultural University, Beijing, China.
Yan-Jie Wu
Ming Zhu
Sheng-Bo Fan
Jinzhong Lin
Kun Zhang
Shuang Li
Hao Chi
Yu-Xin Li
Hai-Feng Chen
Shu-Kun Luo
Yue-He Ding
Le-Heng Wang
Zhiqi Hao
Li-Yun Xiu
She Chen
Keqiong Ye
Si-Min He
Meng-Qiu Dong

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We have developed pLink, software for data analysis of cross-linked proteins coupled with mass-spectrometry analysis. pLink reliably estimates false discovery rate in cross-link identification and is compatible with multiple homo- or hetero-bifunctional cross-linkers. We validated the program with proteins of known structures, and we further tested it on protein complexes, crude immunoprecipitates and whole-cell lysates. We show that it is a robust tool for protein-structure and protein-protein-interaction studies.

Indexed as

AlgorithmsAnimalsCaenorhabditis elegansChromatography, High Pressure LiquidCross-Linking ReagentsDatabases, ProteinData Interpretation, StatisticalEscherichia coliFalse Positive ReactionsHumansMass SpectrometryModels, MolecularPeptidesProtein BindingProtein ConformationProteomicsCross-Linking ReagentsPeptides

Identifiers

PMID22772728

What OpenQuestion holds

Textmetadata
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.