{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Liu CH"],"funding":["National Science and Technology Council","China Medical University","China Medical University Hospital"],"pagination":["W390-W397"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11223864"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["52(W1)"],"pubmed_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"],"journal":["Nucleic acids research"],"pubmed_title":["LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis."],"pmcid":["PMC11223864"],"funding_grant_id":["CMU111-IP-04","DMR-113-191","DMR-113-190","NSTC 112-2311-B-039 -001","DMR-112-056","NSTC 112-2622-E-039 -001","CMU112-MF-25"],"pubmed_authors":["Liu CH","Hung MC","Chen IC","Lin WJ","Lai YL","Huang TY","Wang YD","Shen PC","Tsai MH","Liu HC","Cheng WC"],"additional_accession":[]},"is_claimable":false,"name":"LipidSig 2.0: integrating lipid characteristic insights into advanced lipidomics data analysis.","description":"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","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Jul","modification":"2025-04-04T19:23:41.207Z","creation":"2025-04-04T19:23:41.207Z"},"accession":"S-EPMC11223864","cross_references":{"pubmed":["38709887"],"doi":["10.1093/nar/gkae335"]}}