Evidence map›Paper›PMID 34048582›Full record

ArticleNucleic acids research2021

LipidSig: a web-based tool for lipidomic data analysis.

Wen-Jen Lin, Pei-Chun Shen, Hsiu-Cheng Liu, Yi-Chun Cho, Min-Kung Hsu, I-Chen Lin, Fang-Hsin Chen, Juan-Cheng Yang, Wen-Lung Ma, Wei-Chung Cheng

Abstract read
In one paragraph

Article in Nucleic acids research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing 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

37 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

10 authors.

Wen-Jen LinGraduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.
Pei-Chun ShenResearch Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
Hsiu-Cheng LiuResearch Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
Yi-Chun ChoResearch Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
Min-Kung HsuResearch Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
I-Chen LinGraduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.
Fang-Hsin ChenDepartment of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan.
Juan-Cheng YangChinese Medicine Research and Development Center, China Medical University Hospital, Taichung 40403, Taiwan.
Wen-Lung MaGraduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.
Wei-Chung ChengGraduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.ORCID 0000-0002-1229-4857

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig.

Indexed as

SoftwareAnimalsBiomarkersData MiningFatty AcidsFerroptosisInternetLipid MetabolismLipidomicsLipidsMachine LearningMiceNeoplasmsBiomarkersFatty AcidsLipids

Identifiers

PMID34048582
PMCPMC8262718

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.