{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["8(2)"],"submitter":["Hanelt TN"],"pubmed_abstract":["RNA binding proteins (RBPs) are crucial regulators of gene expression and critically depend on the specific recognition of their target RNAs. Accordingly, a selection of methods to analyze RBP specificities has been developed, including protein-RNA crosslinking and sequencing (CLIP) and in vitro selection methods such as SELEX, RNA compete or RNA bind-n-seq. However, limitations like the availability for purified recombinant proteins and custom microarray platforms (RNAcompete) or extensive sequencing depth and sophisticated bioinformatic data processing (CLIP) may limit a broader implementation of these methods. Here, we present an RNA bind-n-seq method that uses short random RNA pools and enables multiple rounds of selection. This results in strong motif enrichment with low positional va"],"journal":["Life science alliance"],"pagination":["e202402782"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC11612968"],"repository":["biostudies-literature"],"pubmed_title":["Endo-bind-n-seq: identifying RNA motifs of RNA binding proteins isolated from endogenous sources."],"pmcid":["PMC11612968"],"pubmed_authors":["Treiber T","Lehmann G","Reichelt R","Grohmann D","Schmid G","Zambelli F","Pavesi G","Treiber N","Eichner N","Rothmeier T","Hanelt TN","Meister G"],"additional_accession":[]},"is_claimable":false,"name":"Endo-bind-n-seq: identifying RNA motifs of RNA binding proteins isolated from endogenous sources.","description":"RNA binding proteins (RBPs) are crucial regulators of gene expression and critically depend on the specific recognition of their target RNAs. Accordingly, a selection of methods to analyze RBP specificities has been developed, including protein-RNA crosslinking and sequencing (CLIP) and in vitro selection methods such as SELEX, RNA compete or RNA bind-n-seq. However, limitations like the availability for purified recombinant proteins and custom microarray platforms (RNAcompete) or extensive sequencing depth and sophisticated bioinformatic data processing (CLIP) may limit a broader implementation of these methods. Here, we present an RNA bind-n-seq method that uses short random RNA pools and enables multiple rounds of selection. This results in strong motif enrichment with low positional va","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Feb","modification":"2025-04-04T00:23:17.6Z","creation":"2025-04-04T00:23:17.6Z"},"accession":"S-EPMC11612968","cross_references":{"pubmed":["39622621"],"doi":["10.26508/lsa.202402782"]}}