Evidence map›Paper›PMID 34568278›Full record

ArticleFrontiers in chemistry2021

HepParser: An Intelligent Software Program for Deciphering Low-Molecular-Weight Heparin Based on Mass Spectrometry.

Hui Wang, Yu Wang, Meijie Hou, Chunming Zhang, Yaojun Wang, Zhendong Guo, Dongbo Bu, Yan Li, Chuncui Huang, Shiwei Sun

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 43% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

10 authors at 4 institutions in 1 country.

Hui WangKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Yu WangKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Meijie HouKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Chunming ZhangKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Yaojun WangCollege of Information and Electrical Engineering, China Agricultural University, Beijing, China.
Zhendong GuoUniversity of Chinese Academy of Sciences, Beijing, China.
Dongbo BuKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Yan LiUniversity of Chinese Academy of Sciences, Beijing, China.
Chuncui HuangUniversity of Chinese Academy of Sciences, Beijing, China.
Shiwei SunKey Lab of Intelligent Information Processing, State Key Lab of Computer Architecture, Big-data Academy, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Chinese Academy of Sciences · CNUniversity of Chinese Academy of Sciences · CNInstitute of Computing Technology · CNInstitute of Biophysics · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-molecular-weight heparins (LMWHs) are considered to be the most successful carbohydrate-based drugs because of their wide use as anticoagulants in clinics. The efficacy of anticoagulants made by LMWHs mainly depends on the components and structures of LMWHs. Therefore, deciphering the components and identifying the structures of LMWHs are critical to developing high-efficiency anticoagulants. However, most LMWHs are mixtures of linear polysaccharides which are comprised of several disaccharide repeating units with high similarity, making it extremely challenging to separate and decipher each component in LMWHs. Here, we present a new algorithm named hepParser to decipher the main components of LMWHs automatically and precisely based on the liquid chromatography/mass spectrometry (LC/MS) data. When tested on the general LMWH using hepParser, profiling of the oligosaccharides with different degrees of polymerization (dp's) was completed with high accuracy within 1 minute. When compared with the results of GlycReSoft on heparan sulfate samples, hepParser achieved more comprehensive and reasonable results automatically.

Indexed as

computational methodglycosaminoglycansisotopic distributionLMWHsmass spectrometry

Identifiers

PMID34568278
PMCPMC8458631
OpenAlexW3197265093

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.