Correction to 'Eduomics: a Nextflow pipeline to simulate -omics data for education' [0.03%]
关于"Eduomics：用于教育的模拟-组学数据Nextflow管道"的更正
[This corrects the article DOI: 10.1093/nar/lqag029.]. © The Author(s) 2026. Published by Oxford University Press.
Published Erratum
NAR genomics and bioinformatics. 2026 Apr 2;8(2):lqag038. DOI:10.1093/nargab/lqag038 2026
systemPipeR: a multipurpose workflow management system for reproducible data analysis [0.03%]
系统管道器：用于可重复数据分析的多功能工作流管理系统
Le Zhang,Daniela Cassol,Brendan Gongol et al.
Le Zhang et al.
Workflow management systems (WMS) are essential for creating and automating multi-step data analyses and ensuring the reproducibility of biological insights. Although numerous WMS solutions exist, few provide deep integration of command-lin...
Henrique M Dias,Guilherme Y A Sagawa,Vladimir J Torres-Rodriguez et al.
Henrique M Dias et al.
Understanding orthologous and homeologous relationships among genes informs how evolution and artificial selection have shaped plant genomes of related species to adapt to different niches and produce diverse phenotypes. Grasses are ecologi...
G/C-ending and synonymous codon bias define functional translational programs that shape human tissue and cancer proteomes [0.03%]
G/C结尾和同义密码偏爱性定义了塑造人类组织和癌症蛋白质组的功能翻译程序
Sherif Rashad,Kuniyasu Niizuma
Sherif Rashad
Codon usage bias is a fundamental feature of the genetic code, yet its impact on messenger RNA translation is incompletely defined. Here, we integrate comparative genomics, human tissue proteomes, large cancer cell line, and patient cancer ...
Optimizing genomic language models for promoter prediction: a comparative study of tokenization and cross-species learning [0.03%]
优化基因组语言模型进行启动子预测：词元化和跨物种学习的比较研究
Eyal Hadad,Noia Kogman,Lina Golan et al.
Eyal Hadad et al.
Large Language Models (LLMs) are increasingly applied to genomic tasks, yet core challenges remain concerning tokenization, evaluation, and data scarcity. This study focuses on promoter classification and systematically evaluates four token...
Comparative Study
NAR genomics and bioinformatics. 2026 Mar 12;8(1):lqag025. DOI:10.1093/nargab/lqag025 2026
gplasCC: classification and recovery of plasmids from short-read sequencing data for any bacterial species [0.03%]
GPLASCC：从短读序列数据中对任意细菌物种的质粒进行分类和恢复
Julian A Paganini,Jesse J Kerkvliet,Oscar Jordan et al.
Julian A Paganini et al.
Plasmids play a pivotal role in the spread of antibiotic resistance genes. Accurately reconstructing plasmids often requires long-read sequencing, but bacterial genomic data in publicly accessible repositories have historically been derived...
Eduomics: a Nextflow pipeline to simulate -omics data for education [0.03%]
Eduomics：一个用于教育的模拟-组学数据的Nextflow工作流
Lorenzo Sola,Davide Bagordo,Simone Carpanzano et al.
Lorenzo Sola et al.
Bridging the gap between learning algorithms and biological interpretation remains the central challenge of bioinformatics education. To move students beyond just learning code and acquire higher-order knowledge, educators face a complexity...
MycoMobilome: a community-focused non-redundant database of transposable element consensus sequences for the fungal kingdom [0.03%]
我的Mobilome：一个针对社区的非冗余转座元件共识序列数据库（真菌界）
Tobias Baril,Daniel Croll
Tobias Baril
Transposable elements (TEs) are found in nearly all eukaryotic genomes. Despite significant advances in the sequencing of genomes, TE resources remain sparse, leading to a lack of traceability, reproducibility, and duplication of effort whe...
Interpreting artificial neural networks to detect genome-wide association signals for complex traits [0.03%]
解释人工神经网络以检测复杂性状的全基因组关联信号
Burak Yelmen,Maris Alver,Merve Nur Güler;Estonian Biobank Research Team;Flora Jay et al.
Burak Yelmen et al.
Investigating the genetic architecture of complex diseases is challenging due to the multifactorial interplay of genomic and environmental influences. Although GWAS have identified thousands of variants for multiple complex traits, conventi...
Sequence-based modeling of low-affinity transcription factor-DNA binding through deep learning [0.03%]
基于深度学习的低亲和力转录因子-DNA结合的序列模型预测
Yingfei Wang,Jinsen Li,Tsu-Pei Chiu et al.
Yingfei Wang et al.
Multiple layers of molecular determinants and mechanisms affect binding specificity between transcription factors (TFs) and DNA. DNA sequence-based deep learning models using convolutional neural networks (CNNs) and self-attention (SA) tran...