Janusz Marek Bujnicki

This study identifies a nucleolar role for Drosophila Argonaute 1, showing it associates with snoRNP machinery and regulates pre-rRNA levels and cell growth.

SQUARNA improves RNA secondary structure prediction by combining stem maximization with free energy minimization, outperforming existing methods including deep learning models.

RNAcentral integrates literature and gene-level data to enhance non-coding RNA sequence analysis and functional understanding.

This paper evaluates blind predictions of dynamic water and ion ensembles around RNA using cryo-EM densities from CASP16, finding that molecular dynamics approaches perform best.

The paper systematically surveys GNRA tetraloop-like motifs in nucleic acid 3D structures, identifying twelve recurrent backbone topology variants and their interactions.

ARTEM identifies RNA and DNA tertiary motifs by searching structural databases, revealing new kink-turn variants and their functional implications.

The paper reports the crystal structure of fungal Trl1-LIG with a tRNA substrate, revealing conserved binding principles and RNA end specificity.

ClaPNAC classifies nucleic acid-protein contacts in 3D structures using geometric features, distinguishing stacking, pseudo pairs, and phosphate/ribose interactions.

This study identifies YTHDF paralogs and VIRMA as major tumor drivers among m6A core genes through a pan-cancer analysis of 10,000 samples.

ARTEMIS improves RNA 3D structure superposition and alignment, revealing conserved helical motifs across non-coding RNAs with sequence permutations.

DEGRONOPEDIA provides a web server for analyzing degron motifs across seven model organisms, integrating sequence, structure, and modification data to support degron research.

RNA Masonry assembles RNA fragments into geometrically plausible models using secondary structure constraints and SAXS data.

SQUARNA is an RNA secondary structure prediction method that uses a greedy stem formation model, performing competitively on single sequences and outperforming existing tools on sequence alignment inputs.

The paper surveys long-range tertiary interactions and motifs in non-coding RNA structures, identifies three common interaction types, and introduces a new dataset and algorithm for their analysis.

DesiRNA designs RNA sequences with a Monte Carlo approach, considering structural and sequence constraints, and performs well on the EteRNA benchmark.

The paper develops SIFt-based machine learning models to predict RNA-ligand binding and provides a benchmark dataset for virtual screening.

The paper introduces fingeRNAt, a tool for detecting non-covalent interactions in nucleic acid-ligand complexes and presents its applications for high-throughput analysis and similarity measurement.

The paper reports RNA 3D structure prediction results for SARS-CoV-2 5'- and 3'-UTRs using computational methods and expert analysis.

AnnapuRNA is a scoring function for predicting RNA-small molecule interactions, outperforming existing tools by using statistical data from experimental RNA-ligand complexes.

The paper systematically explores RNA-ligand interactions by analyzing mutations in an RNA aptamer, revealing complex phenotypic effects and training a model to predict RNA structure from epistasis.

This study maps SARS-CoV-2 RNA structures at single-base resolution using SHAPE-MaP, identifies druggable pockets and conserved elements, and highlights targets for antisense therapeutics.

The paper investigates RNA-chaperone activity of OB-fold proteins in the Trypanosoma brucei editosome, showing activity differences correlate with surface areas and intrinsically disordered subdomains.