Jun 23 2022 Hfq, Crc, and antibiotic resistance in P. aeruginosa

Here we study carbon catabolite repression (CCR) and its impact on antibiotic susceptibility in Pseudomonas aeruginosa

Feb 03 2022 Japanese encephalitis virus genome cyclization is kinetically driven

This study uses biophysical and bioinformatics methods to assess the long-range RNA-RNA interaction between terminal regions of Japanese encephalitis virus

Jan 20 2022 Biophysical characterisation of human lincRNA-p21 Alu inverted repeats

In this study we determine the tertiary structure of human LincRNA-p21 Alu Inverted Repeats with biophysical and computational approaches

Dec 17 2021 RNA structure conservation and molecular epidemiology of TBEV

In this paper, we study the molecular epidemiology and RNA structureome diversity of tick-borne encephalitis virus (TBEV). Moreover, we propose a unified picture of pervasive non-coding RNA structure conservation across all known TBEV subtypes

Dec 16 2021 Deep learning methods are unable to predict RNA secondary structures

RNA structure prediction might seem like an ideal fit for machine learning, but it's more challenging than you might think. In this paper, we explore these difficulties by using synthetic data generated by ViennaRNA's RNAfold, offering a controlled environment to study how neural networks handle RNA secondary structure prediction. What we found suggests that the limitations seen in artificial settings can directly translate to real-world data, raising important questions about the effectiveness of current machine learning approaches in this field.