NLM DIR Seminar Schedule
UPCOMING SEMINARS
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April 22, 2025 Stanley Liang, PhD
Large Vision Model for medical knowledge adaptation -
April 29, 2025 Pascal Mutz
Characterization of covalently closed cirular RNAs detected in (meta)transcriptomic data -
May 2, 2025 Dr. Lang Wu
Integration of multi-omics data in epidemiologic research -
May 6, 2025 Leslie Ronish
TBD -
May 8, 2025 MG Hirsch
TBD
RECENT SEMINARS
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April 18, 2025 Valentina Boeva, Department of Computer Science, ETH Zurich
Decoding tumor heterogeneity: computational methods for scRNA-seq and spatial omics -
April 8, 2025 Jaya Srivastava
Leveraging a deep learning model to assess the impact of regulatory variants on traits and diseases -
April 1, 2025 Roman Kogay
Horizontal transfer of bacterial operons into eukaryote genomes -
March 25, 2025 Yifan Yang
Adversarial Manipulation and Data Memorization in Large Language Models for Medicine -
March 11, 2025 Sofya Garushyants
Tmn – bacterial anti-phage defense system
Scheduled Seminars on April 29, 2025
In-person: Building 38A/B2N14 NCBI Library or Meeting Link
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Covalently closed circular RNAs (cccRNA) are involved in various cellular processes and are the genomic template of viroids and viroid-like elements such as Ribozyviria (including Hepatitis Delta Virus, HDV), virusoids, ambiviruses or the recently discovered obelisks. Although their presence across eukaryotes and archaea and as infectious agents, their abundance as well as variety is far from being understood, including completely undiscovered entities as seen with recently discovered obelisks.
I will present our preliminary results characterizing nearly 9 million putative cccRNA found in (meta)transcriptomic data by a recently developed pipeline in our group. The majority of cccRNAs is rather small with 75% below 250 nt but largest ones are thousands of nucleotides long. Predicting open reading frames revealed nearly 5 million encoding for putative proteins of at least 60 aa. Subsequent protein clustering, annotation and structure prediction of proteins encoded by at least two independent cccRNAs was used to characterize the putative proteins. Putative cellular proteins encoded by cccRNAs were linked to their likely cellular role by KEGG pathways annotation and putative viral proteins were examined. Interestingly, a handful of putative proteins encoded by at least 10 cccRNAs showed good structure prediction and a globular fold but no relationship with known proteins, indicating the presence of newly discovered cccRNA entities. To classify the cccRNA itself, we started to predict RNA secondary structures to identify abundant folds which can represent new classes of Ribozymes.