bioRxiv Science⌕ Search

Biology subjects

Grieco, M.

Publications and source records attributed to Grieco, M..

2 recordsLinked to original sources

RNAMaRs: an interpretable framework for inferring multivalent RNA Motifs and cognate Regulators of Splicing

Alternative splicing expands proteomic diversity and is shaped by interactions between RNA-binding proteins (RBPs) and multivalent RNA motifs. Linking sequence elements to regulatory proteins remains difficult from sequence information alone. Here we present RNAMaRs, a interpretable statistical framework that combines motif discovery with in vivo binding and splicing responses to infer motif-RBP relationships. RNAMaRs learns RBP binding principles, weights signal quality, and optimizes motif discovery in an RBP-specific manner. Across ENCODE datasets RNAMaRs consistently prioritizes the perturbed regulator, especially for large splicing effects. Independent validation in prostate cancer cells recapitulates HNRNPK binding signatures, supporting transferability across an unseen cellular context.

molecular biology↗

Kandinsky: enabling neighbourhood analysis of spatial omics data for functional insights on cell ecosystems

Spatially resolved omics technologies enable investigation of how cells interact within their local environments or neighbourhoods directly in situ. Although a few computational methods have been developed to aid this analysis, significant limitations still exist in the way neighbourhoods are defined and exploited for downstream analyses. Here, we present Kandinsky, a computational tool that implements multiple approaches for neighbourhood identification, enabling high flexibility and versatility to address a variety of biological questions. Once identified, Kandinsky applies neighbourhoods for downstream studies, including proximity-based cell grouping for functional comparisons, spatial co-localisation and dispersion, and identification of hot and cold expression areas within the tissue. We apply Kandinsky to transcriptomic and proteomic data from different spatial technologies to showcase how it can reveal functional interactions between cells across multiple biological contexts. Availability and implementationKandinsky is freely available as an R package at https://github.com/ciccalab/Kandinsky.

bioinformatics↗