The 5'-3' distance of RNA secondary structures.

J Comput Biol

Institut for Matematik og Datalogi, University of Southern Denmark, Odense, Denmark.

Published: July 2012

Recently, Yoffe and colleagues observed that the average distances between 5'-3' ends of RNA molecules are very small and largely independent of sequence length. This observation is based on numerical computations as well as theoretical arguments maximizing certain entropy functionals. In this article, we compute the exact distribution of 5'-3' distances of RNA secondary structures for any finite n. Furthermore, we compute the limit distribution and show that for n = 30 the exact distribution and the limit distribution are very close. Our results show that the distances of random RNA secondary structures are distinctively lower than those of minimum free energy structures of random RNA sequences.

Download full-text PDF

Source
http://dx.doi.org/10.1089/cmb.2011.0301DOI Listing

Publication Analysis

Top Keywords

rna secondary
12
secondary structures
12
exact distribution
8
limit distribution
8
random rna
8
rna
5
5'-3' distance
4
distance rna
4
structures
4
structures yoffe
4

Similar Publications

CXCR4 promotes tumor stemness maintenance and CDK4/6 inhibitors resistance in ER-positive breast cancer.

Breast Cancer Res

January 2025

Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, 510120, China.

Background: CDK4/6 inhibitors have significantly improved the survival of patients with HR-positive/HER2-negative breast cancer, becoming a first-line treatment option. However, the development of resistance to these inhibitors is inevitable. To address this challenge, novel strategies are required to overcome resistance, necessitating a deeper understanding of its mechanisms.

View Article and Find Full Text PDF

Transcriptome analysis of nitrate enhanced tobacco resistance to aphid infestation.

Plant Physiol Biochem

January 2025

School of Agriculture and Biotechnology, Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, Guangdong, China. Electronic address:

Tobacco is an economic crop that primarily relies on nitrate (NO) as its nitrogen source, and tobacco aphid is one of the significant pests that harm its growth. However, the impact of NO supply on the resistance of tobacco to aphids remains unclear. Present study investigated the effects of different NO concentrations supply on the reproductive capacity of tobacco aphids, impact of aphid infestation on tobacco growth, secondary metabolic and transcription changes.

View Article and Find Full Text PDF

Stereocaulon alpinum has been found to have potential pharmaceutical properties due to the presence of secondary metabolites such as usnic acid, atranorin, and lobaric acid (LA) which have anticancer activity. On the other hand, the effect of LA on the stemness potential of colorectal cancer (CRC) cells remains unexplored, and has not yet been thoroughly investigated. In this study, we examined the inhibitory activity of LA from Stereocaulon alpinum against the stemness potential of CRC cells and investigated the possible underlying mechanisms.

View Article and Find Full Text PDF

Tofacitinib Treatment for Active Dermatomyositis and Anti-synthetase Syndrome: A Prospective Cohort Pilot Study.

Rheumatology (Oxford)

January 2025

Department of Rheumatology and Immunology and Beijing Key Laboratory for Rheumatism and Immune Diagnosis (BZ0135), Peking University People's Hospital, Beijing, 100044, China.

Objectives: The objective of this study was to evaluate the efficacy and safety of tofacitinib in the treatment of active dermatomyositis (DM) and anti-synthetase syndrome (ASS).

Methods: Tofacitinib was administered at a dose of 5 mg twice daily to patients who exhibited inadequate response to conventional treatments. The primary end point was the reduction of T follicular helper (Tfh) cells at week 24.

View Article and Find Full Text PDF

The growing demand for biological products drives many efforts to maximize expression of heterologous proteins. Advances in high-throughput sequencing can produce data suitable for building sequence-to-expression models with machine learning. The most accurate models have been trained on one-hot encodings, a mechanism-agnostic representation of nucleotide sequences.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!