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Nancy Ontiveros‐Palacios

European Bioinformatics Institute

ORCID: 0000-0001-8457-4455

Publishes on RNA and protein synthesis mechanisms, RNA modifications and cancer, Genomics and Phylogenetic Studies. 18 papers and 1.6k citations.

18Publications
1.6kTotal Citations

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Top publicationsby citations

Rfam 14: expanded coverage of metagenomic, viral and microRNA families
Ioanna Kalvari, Eric P. Nawrocki, Nancy Ontiveros‐Palacios et al.|Nucleic Acids Research|2020
Cited by 1.1kOpen Access

Rfam is a database of RNA families where each of the 3444 families is represented by a multiple sequence alignment of known RNA sequences and a covariance model that can be used to search for additional members of the family. Recent developments have involved expert collaborations to improve the quality and coverage of Rfam data, focusing on microRNAs, viral and bacterial RNAs. We have completed the first phase of synchronising microRNA families in Rfam and miRBase, creating 356 new Rfam families and updating 40. We established a procedure for comprehensive annotation of viral RNA families starting with Flavivirus and Coronaviridae RNAs. We have also increased the coverage of bacterial and metagenome-based RNA families from the ZWD database. These developments have enabled a significant growth of the database, with the addition of 759 new families in Rfam 14. To facilitate further community contribution to Rfam, expert users are now able to build and submit new families using the newly developed Rfam Cloud family curation system. New Rfam website features include a new sequence similarity search powered by RNAcentral, as well as search and visualisation of families with pseudoknots. Rfam is freely available at https://rfam.org.

Rfam 15: RNA families database in 2025
Nancy Ontiveros‐Palacios, Emma J. Cooke, Eric P. Nawrocki et al.|Nucleic Acids Research|2024
Cited by 151Open Access

The Rfam database, a widely used repository of non-coding RNA families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology (GO) and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronization with miRBase, resulting in 1603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam's coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation and the development of machine learning models. Rfam is freely available at https://rfam.org.

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research
Franziska Hufsky, Kevin Lamkiewicz, Alexandre Almeida et al.|Briefings in Bioinformatics|2020
Cited by 148Open Access

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.

Molecular basis of gene regulation by the THI‐box riboswitch
Nancy Ontiveros‐Palacios, Angela M. Smith, Frank J. Grundy et al.|Molecular Microbiology|2007
Cited by 61Open Access

Riboswitches are genetic control elements located mainly within the 5' untranslated regions of messenger RNAs. These RNA elements undergo conformational changes that modulate gene expression upon binding of regulatory signals including vitamins, amino acids, nucleobases and uncharged tRNA. The thiamin pyrophosphate (TPP)-binding riboswitch (THI-box) is found in all three kingdoms of life and can regulate gene expression at the levels of premature termination of transcription, initiation of translation and mRNA splicing. The THI-box is composed of two parallel stacked helices bound by another helix in a three-way junction. We performed an in vivo expression analysis of mutants with substitutions in conserved bases located at the interior and terminal loops of the Escherichia coli thiM THI-box, which is translationally regulated, and observed two different phenotypic classes. One class exhibited high expression during growth in the presence or absence of thiamin, while the second class exhibited low expression regardless of the presence of thiamin. Accessibility of the Shine-Dalgarno region of the RNA following the addition of TPP was monitored by means of an oligonucleotide-dependent RNase H cleavage assay, and binding of 30S ribosomal subunits. These studies showed that high- and low-expression mutant RNAs are locked in the non-repressive and repressive conformations respectively.