Mycobacterium tuberculosis uses intrinsically disordered, fast evolving proteins to interact with conserved host factors [0.03%]
结核分枝杆菌利用内在无序且快速进化的蛋白质与宿主固有因子相互作用
Uberto Pozzoli,Diego Forni,Federica Arrigoni et al.
Uberto Pozzoli et al.
Background: Intrinsically disordered protein regions (IDRs) are implicated in diverse cellular processes in eukaryotes and, in these organisms, they cover up to 40% of the proteome. Surprisingly little is known about IDRs...
Long-read structural variant discovery and targeted short read genotyping enables population scale characterization of structural variation in rhesus macaques [0.03%]
长读取结构变异发现和靶向短读取基因分型可在恒河猴中实现人群规模的结构变异表征
Karina Ray,Christina Mulch,Samuel M Peterson et al.
Karina Ray et al.
Background: Due to their close evolutionary relationship with humans, rhesus macaques are an important pre-clinical model. While genetic diversity driven by short nucleotide variation has long been studied in rhesus macaq...
Structure-enhanced graph meta learning for few-shot gene regulatory network inference [0.03%]
基于结构增强的图元学习的少样本基因调控网络推理方法研究
Weiming Yu,Zhuobin Chen,Yaohua Hu et al.
Weiming Yu et al.
Inferring gene regulatory networks (GRNs) is essential for understanding biological regulation. Although numerous deep learning approaches have been developed for GRN inference, most require large amounts of labeled data. We present Meta-TG...
scSpecies: enhancement of network architecture alignment in comparative single-cell studies [0.03%]
scSpecies：比较单细胞研究中网络架构对齐的增强
Clemens Schächter,Maren Hackenberg,Martin Treppner et al.
Clemens Schächter et al.
Animals can provide meaningful context for human single-cell data. To transfer information between species, we propose a deep learning approach that pre-trains a conditional variational autoencoder on animal data and transfers its final enc...
Cell type-specific inference from bulk RNA-sequencing data by integrating single-cell reference profiles via EPIC-unmix [0.03%]
通过EPIC-unmix整合单细胞参考谱型对批量RNA测序数据进行特异性细胞类型推断
Chenwei Tang,Quan Sun,Xinyue Zeng et al.
Chenwei Tang et al.
Cell type-specific analysis is crucial for uncovering biological insights hidden in bulk tissue data, yet single-cell or single-nuclei approaches are often cost-prohibitive for large samples. We introduce EPIC-unmix, a novel two-step empiri...
Benchmarking deep learning methods for biologically conserved single-cell integration [0.03%]
生物保守的单细胞整合的深度学习方法基准测试
Chenxin Yi,Jinyu Cheng,Jiajun Chen et al.
Chenxin Yi et al.
Background: Advancements in single-cell RNA sequencing have enabled the analysis of millions of cells, but integrating such data across samples and methods while mitigating batch effects remains challenging. Deep learning...
Tian-Neng Zhu,Xing Huang,Meng-Yuan Yang et al.
Tian-Neng Zhu et al.
To reach a genomic scale illustration for linkage disequilibrium (LD), we introduce X-LDR, a stochastic algorithm for biobank-scale data ([Formula: see text], n the sample size, m the number of SNPs, and B iterations). X-LDR can scale the e...
Double-stranded DNA deaminase DddAE1347A can increase the efficiency and targeting range of cytidine base editors [0.03%]
双链DNA脱氨酶DddAE1347A可增强胞苷碱基编辑的效率和靶向范围
Yuqiang Qian,Fengjiao Hui,Wenchao Niu et al.
Yuqiang Qian et al.
Background: Cytidine base editors (CBEs) consist of a single-strand specific cytidine deaminase fused to Cas9 nickase, enabling efficient C-to-T conversion across diverse organisms. Enhancing editing range and efficiency ...
DeepCOI: a large language model-driven framework for fast and accurate taxonomic assignment in animal metabarcoding [0.03%]
基于大型语言模型的动物元条码鉴定快速且准确的赋税框架
Ho-Jin Gwak,Mina Rho
Ho-Jin Gwak
Metabarcoding remains challenging due to incomplete taxonomic annotations and computationally intensive processes. We present DeepCOI, a large language model-based classifier pre-trained on seven million cytochrome c oxidase I gene sequence...
A Burak Gulhan,Richard Burhans,Robert Harris et al.
A Burak Gulhan et al.
Advances in sequencing and assembly allow the creation of thousands of genome assemblies. However, producing multiple alignments required for their analysis lags behind due to the time-consuming process of pairwise alignment, typically perf...