{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9"],"submitter":["Yang M"],"funding":["Earmarked Fund for China Agriculture Research System","Central Public-interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences","National Key Research and Development Program of China"],"pubmed_abstract":["<i>Porphyra dentata</i> is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that <i>P. dentata</i> is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomics was first applied to identify and characterize different harvest proteins in <i>P. dentata.</i> A total of 13,046 different peptides were identified and 419 co-expression target proteins were characterized. Bioinformatics was used to study protein characteristics, functional expression, and interaction of two important functional annotations, amino acid, and carbohydrate metabolism. Potential bioactive peptides, protein structure, and potential ligand conformations were predicted"],"journal":["Frontiers in nutrition"],"pagination":["924524"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9301277"],"repository":["biostudies-literature"],"pubmed_title":["Bioinformatic Prediction and Characterization of Proteins in <i>Porphyra dentata</i> by Shotgun Proteomics."],"pmcid":["PMC9301277"],"pubmed_authors":["Yang X","Ma L","Li C","Yang M","Chen S","Qi B","Wang Y","Li L","Yang S","Zhao Y"],"additional_accession":[]},"is_claimable":false,"name":"Bioinformatic Prediction and Characterization of Proteins in <i>Porphyra dentata</i> by Shotgun Proteomics.","description":"<i>Porphyra dentata</i> is an edible red seaweed with high nutritional value. It is widely cultivated and consumed in East Asia and has vast economic benefits. Studies have found that <i>P. dentata</i> is rich in bioactive substances and is a potential natural resource. In this study, label-free shotgun proteomics was first applied to identify and characterize different harvest proteins in <i>P. dentata.</i> A total of 13,046 different peptides were identified and 419 co-expression target proteins were characterized. Bioinformatics was used to study protein characteristics, functional expression, and interaction of two important functional annotations, amino acid, and carbohydrate metabolism. Potential bioactive peptides, protein structure, and potential ligand conformations were predicted","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2026-05-09T16:37:41.036Z","creation":"2024-11-13T08:39:36.818Z"},"accession":"S-EPMC9301277","cross_references":{"pubmed":["35873412"],"doi":["10.3389/fnut.2022.924524"]}}