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LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.
Liu, Chia-Hsin; Shen, Pei-Chun; Lin, Wen-Jen; Liu, Hsiu-Cheng; Tsai, Meng-Hsin; Huang, Tzu-Ya; Chen, I-Chieh; Lai, Yo-Liang; Wang, Yu-De; Hung, Mien-Chie; Cheng, Wei-Chung.
Afiliación
  • Liu CH; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Shen PC; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Lin WJ; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Liu HC; School of Medicine, China Medical University, Taichung 404328, Taiwan.
  • Tsai MH; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Huang TY; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Chen IC; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Lai YL; Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
  • Wang YD; Department of Radiation Oncology, China Medical University, Taichung 404328, Taiwan.
  • Hung MC; Graduate Institute of Biomedical Sciences, China Medical University, Taichung 404328, Taiwan.
  • Cheng WC; Department of Urology, China Medical University, Taichung 404328, Taiwan.
Nucleic Acids Res ; 52(W1): W390-W397, 2024 Jul 05.
Article en En | MEDLINE | ID: mdl-38709887
ABSTRACT
In the field of lipidomics, where the complexity of lipid structures and functions presents significant analytical challenges, LipidSig stands out as the first web-based platform providing integrated, comprehensive analysis for efficient data mining of lipidomic datasets. The upgraded LipidSig 2.0 (https//lipidsig.bioinfomics.org/) simplifies the process and empowers researchers to decipher the complex nature of lipids and link lipidomic data to specific characteristics and biological contexts. This tool markedly enhances the efficiency and depth of lipidomic research by autonomously identifying lipid species and assigning 29 comprehensive characteristics upon data entry. LipidSig 2.0 accommodates 24 data processing methods, streamlining diverse lipidomic datasets. The tool's expertise in automating intricate analytical processes, including data preprocessing, lipid ID annotation, differential expression, enrichment analysis, and network analysis, allows researchers to profoundly investigate lipid properties and their biological implications. Additional innovative features, such as the 'Network' function, offer a system biology perspective on lipid interactions, and the 'Multiple Group' analysis aids in examining complex experimental designs. With its comprehensive suite of features for analyzing and visualizing lipid properties, LipidSig 2.0 positions itself as an indispensable tool for advanced lipidomics research, paving the way for new insights into the role of lipids in cellular processes and disease development.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Lipidómica / Lípidos Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Lipidómica / Lípidos Idioma: En Revista: Nucleic Acids Res Año: 2024 Tipo del documento: Article País de afiliación: Taiwán
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