Proteomics

Dataset Information

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Dynamic maps of protein-protein-metabolite complexes of Arabidopsis Thaliana seedlings

ABSTRACT: The project aimed to create dynamic maps of protein-protein-metabolite complexes of Arabidopsis thaliana seedlings using PROMIS (PROtein–Metabolite Interactions using Size separation). The approach involves using size exclusion chromatography (SEC) to separate complexes, followed by LC-MS-based proteomics and metabolomics analysis of the obtained fractions. Co-elution is used to reconstruct the protein-metabolite interactions (PMIs) networks. PROMIS strongly progresses understanding protein-small molecule interactions due to its non-targeted manner, cell-wide scale, and generic nature, making it suitable across biological systems. Combining PROMIS with mashing learning approach SLIMP “supervised learning of metabolite-protein interactions from multiple co-fractionation mass spectrometry datasets” allows computing a global map of metabolite-protein interactions in vivo.

INSTRUMENT(S):

ORGANISM(S): Arabidopsis Thaliana (mouse-ear Cress)

TISSUE(S): Seedling

SUBMITTER: Ewelina Sokolowska  

LAB HEAD: Aleksandra Skirycz

PROVIDER: PXD026713 | Pride | 2022-10-14

REPOSITORIES: Pride

Json Xml

Dataset's files

Source:
Action DRS
PROMIS_seedlings_proteinGroups.txt Txt
checksum.txt Txt
evidence.txt Txt
parameters.txt Txt
peptides.txt Txt
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Publications

Long intergenic noncoding RNAs (lincRNAs) are a large yet enigmatic class of eukaryotic transcripts that can have critical biological functions. The wealth of RNA-sequencing (RNA-seq) data available for plants provides the opportunity to implement a harmonized identification and annotation effort for lincRNAs that enables cross-species functional and genomic comparisons as well as prioritization of functional candidates. In this study, we processed >24 Tera base pairs of RNA-seq data from >16,00  ...[more]

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