The interaction between RNA and RNA-binding proteins (RBPs) has a key role in the regulation of gene expression, in RNA stability, and in many other biological processes. RBPs accomplish these functions by binding target RNA molecules through specific sequence and structure motifs. The identification of these binding motifs is therefore fundamental to improve our knowledge of the cellular processes and how they are regulated. Here, we present BRIO (BEAM RNA Interaction mOtifs), a new web server designed for the identification of sequence and structure RNA-binding motifs in one or more RNA molecules of interest. BRIO enables the user to scan over 2508 sequence motifs and 2296 secondary structure motifs identified in Homo sapiens and Mus musculus, in three different types of experiments (PAR-CLIP, eCLIP, HITS). The motifs are associated with the binding of 186 RBPs and 69 protein domains. The web server is freely available at http://brio.bio.uniroma2.it.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262756 | PMC |
http://dx.doi.org/10.1093/nar/gkab400 | DOI Listing |
Crit Rev Oncog
January 2025
GITAM.
Coralyne (COR) is a protoberberine-like isoquinoline alkaloid, and it is known for double-stranded (ds) DNA intercalation and topoisomerase inhibition. It can also sensitize cancer cells through various mechanisms. COR reduces the proliferation and migration of breast cancer cells by inhibiting the expression and activity of matrix metalloproteinase 9 (MMP9).
View Article and Find Full Text PDFPeerJ
January 2025
Department of Computer Science, Virginia Polytechnic Institute and State University (Virginia Tech), Blacksburg, VA, United States of America.
Despite the recent surge of viral metagenomic studies, it remains a significant challenge to recover complete virus genomes from metagenomic data. The majority of viral contigs generated from de novo assembly programs are highly fragmented, presenting significant challenges to downstream analysis and inference. To address this issue, we have developed Virseqimprover, a computational pipeline that can extend assembled contigs to complete or nearly complete genomes while maintaining extension quality.
View Article and Find Full Text PDFAdv Sci (Weinh)
January 2025
Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China.
Protein phosphorylation plays a crucial role in regulating a wide range of biological processes, and its dysregulation is strongly linked to various diseases. While many phosphorylation sites have been identified so far, their functionality and regulatory effects are largely unknown. Here, a deep learning model MMFuncPhos, based on a multi-modal deep learning framework, is developed to predict functional phosphorylation sites.
View Article and Find Full Text PDFHardwareX
March 2025
INRAE - French National Research Institute for Agriculture, Food and Environment, REVERSAAL Research Unit, 5 rue de la Doua, CS 20244, 69625 Villeurbanne Cedex, France.
Sensors play an important role in both the continuous monitoring and intermittent analyses, which are essential for the study of wastewater treatment plant management and conducting related research. Given the significant environmental impact of the issues involved, accurate measurement of the volume of water flowing into and out of treatment plants is a key parameter for plant management, ecotoxicological studies and academic research programs. Traditionally, flow measurements have been based on calibrated weirs or venturi flumes, using water level measurements for conversion into flow, according to established relationships.
View Article and Find Full Text PDFBioinformatics
January 2025
Biocomputing Group, University of Bologna, Italy.
Motivation: The knowledge of protein stability upon residue variation is an important step for functional protein design and for understanding how protein variants can promote disease onset. Computational methods are important to complement experimental approaches and allow a fast screening of large datasets of variations.
Results: In this work we present DDGemb, a novel method combining protein language model embeddings and transformer architectures to predict protein ΔΔG upon both single- and multi-point variations.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!