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LipidSig: a web-based tool for lipidomic data analysis.
Lin, Wen-Jen; Shen, Pei-Chun; Liu, Hsiu-Cheng; Cho, Yi-Chun; Hsu, Min-Kung; Lin, I-Chen; Chen, Fang-Hsin; Yang, Juan-Cheng; Ma, Wen-Lung; Cheng, Wei-Chung.
Afiliación
  • Lin WJ; Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.
  • Shen PC; Research Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
  • Liu HC; Research Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
  • Cho YC; Research Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
  • Hsu MK; Research Center for Cancer Biology, China Medical University, Taichung 40403, Taiwan.
  • Lin IC; Graduate Institute of Biomedical Science, China Medical University, Taichung 40403, Taiwan.
  • Chen FH; Department of Medical Imaging and Radiological Sciences, Chang Gung University, Taoyuan 33302, Taiwan.
  • Yang JC; Department of Radiation Oncology, Chang Gung Memorial Hospital at Linkou, Taoyuan 33302, Taiwan.
  • Ma WL; Institute for Radiological Research, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan 33302, Taiwan.
  • Cheng WC; Chinese Medicine Research and Development Center, China Medical University Hospital, Taichung 40403, Taiwan.
Nucleic Acids Res ; 49(W1): W336-W345, 2021 07 02.
Article en En | MEDLINE | ID: mdl-34048582
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Lipidómica Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Lipidómica Tipo de estudio: Prognostic_studies Límite: Animals Idioma: En Revista: Nucleic Acids Res Año: 2021 Tipo del documento: Article País de afiliación: Taiwán
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