RNAcentral in 2026: Genes and literature integration
Andrew Green, Carlos Eduardo Ribas, Isaac Jandalala…·Blake Sweeney
RNAcentral integrates literature and gene-level data to enhance non-coding RNA sequence analysis and functional understanding.
Author
Chinese Academy of SciencesORCID 0000-0002-7294-0865Unclaimed ORCID profile · follow to get notified of new preprints
8 papers
Recent·Most cited
Andrew Green, Carlos Eduardo Ribas, Isaac Jandalala…·Blake Sweeney
RNAcentral integrates literature and gene-level data to enhance non-coding RNA sequence analysis and functional understanding.
Yuanxin Wang, Jiajia Wang, Yanyan Li…·Shunmin He
This study analyzes mitochondrial DNA variants and nuclear mitochondrial DNA segments in 7331 individuals from NyuWa and 1KGP, identifying common and ultra-rare NUMTs and linking mtDNA variants to nuclear DNA variants.
Shuai Liu, Yanyan Li, Tingrui Song…·Shunmin He
The paper investigates HLA allele adaptation to pathogens and its correlation with autoimmune diseases in Han Chinese individuals, identifying specific alleles linked to both pathogen resistance and disease susceptibility.
Peng Zhang, Huaxia Luo, Yanyan Li…·Shunmin He
The paper presents the NyuWa genome resource, a Chinese population-specific reference panel built from deep whole genome sequencing, which improves imputation accuracy and identifies novel variants.
Yanyan Li, Honghong Zhou, Xiaomin Chen…·Shunmin He
SmProt provides a comprehensive and reliable repository of small proteins identified from ribosome profiling, including curated data from multiple species and sources.
Yiwei Niu, Xueyi Teng, Yirong Shi…·Shunmin He
The paper reports a comprehensive map of 36,699 non-reference mobile element insertions (MEIs) from 5,675 human genomes and builds a database for public use.
Yajing Hao, Dongpeng Wang, Shuheng Wu…·Shunmin He
The paper shows that active retrotransposons produce siRNAs that maintain pericentromeric heterochromatin, ensuring stable genetic inheritance in Drosophila cells.
Ya Cui, Yiwei Niu, Xueyi Teng…·Runsheng Chen
Ennet identifies cancer-driving networks using somatic enhancer mutations, revealing known and novel networks across multiple cancer types.