A BAC-guided haplotype assembly pipeline increases the resolution of the virus resistance locus CMD2 in cassava [0.03%]
一种BAC指导的基因型组装管线提高了 cassava 对病毒CMD2 位点解析度
Luc Cornet,Syed Shan-E-Ali Zaidi,Jia Li et al.
Luc Cornet et al.
Background: Cassava is an important crop for food security in the tropics where its production is jeopardized by several viral diseases, including the cassava mosaic disease (CMD) which is endemic in Sub-Saharan Africa an...
Kelly Yichen Li,Qin Cao,Savio Ho-Chit Chow et al.
Kelly Yichen Li et al.
Background: Transcriptional enhancers usually, but not always, regulate genes within the same topologically associating domain (TAD). We hypothesize that this incomplete insulation is partially due to three-dimensional st...
Geometric Diagrams of Genomes: constructing a visual grammar for 3D genomics [0.03%]
基因组的几何图谱：构建三维基因组的视觉语法
Carla Molins-Pitarch,Jonathan Khao,Santiago Bonet et al.
Carla Molins-Pitarch et al.
Advances in the field of three-dimensional (3D) genomics have revealed an ever-expanding array of architectural features that were unknown only a few years ago. Just as ribbon diagrams integrate spatial and symbolic representation to commun...
Jeremy A Arbesfeld,Estelle Y Da,James S Stevenson et al.
Jeremy A Arbesfeld et al.
Background: Experimental data from functional assays have a critical role in interpreting the impact of genetic variants. Assay data must be unambiguously mapped to a reference genome to make it accessible, but it is ofte...
spCLUE: a contrastive learning approach to unified spatial transcriptomics analysis across single-slice and multi-slice data [0.03%]
基于对比学习的空间转录组学跨单切片和多切片数据统一分析方法
Xiang Wang,Wei Vivian Li,Hongwei Li
Xiang Wang
Advances in spatial transcriptomics demand new tools to integrate data across tissue slices and identify consistent spatial domains. We introduce spCLUE, a comprehensive framework combining multi-view graph network, contrastive learning, at...
CellMemory: hierarchical interpretation of out-of-distribution cells using bottlenecked transformer [0.03%]
基于瓶颈变压器的异常单元的层次化解释(CellMemory)
Qifei Wang,He Zhu,Yiwen Hu et al.
Qifei Wang et al.
Machine learning methods, especially Transformer architectures, have been widely employed in single-cell omics studies. However, interpretability and accurate representation of out-of-distribution (OOD) cells remains challenging. Inspired b...
Loop Catalog: a comprehensive HiChIP database of human and mouse samples [0.03%]
循环目录：人类和小鼠样本的全面HiChIP数据库
Joaquin Reyna,Kyra Fetter,Romeo Ignacio et al.
Joaquin Reyna et al.
HiChIP enables cost-effective and high-resolution profiling of chromatin loops. To leverage the increasing number of HiChIP datasets, we develop Loop Catalog ( https://loopcatalog.lji.org ), a web-based database featuring loop calls from ov...
Comparison of spatial transcriptomics technologies using tumor cryosections [0.03%]
基于肿瘤冷冻切片的类空间转录组技术比较研究
Anne Rademacher,Alik Huseynov,Michele Bortolomeazzi et al.
Anne Rademacher et al.
Background: Spatial transcriptomics technologies are revolutionizing our understanding of intra-tumor heterogeneity and the tumor microenvironment by revealing single-cell molecular profiles within their spatial tissue co...
scExtract: leveraging large language models for fully automated single-cell RNA-seq data annotation and prior-informed multi-dataset integration [0.03%]
基于大型语言模型的单细胞RNA序列数据全自动注释和先验知识引导多数据集集成工具scExtract
Yuxuan Wu,Fuchou Tang
Yuxuan Wu
Single-cell RNA sequencing has revolutionized cellular heterogeneity research, but analyzing the abundance of unannotated public datasets remains challenging. We present scExtract, a framework leveraging large language models to automate sc...
KPop: accurate and scalable comparative analysis of microbial genomes by sequence embeddings [0.03%]
基于序列嵌入的准确可扩展的微生物基因组比较分析(KPop)
Xavier Didelot,Paolo Ribeca
Xavier Didelot
Here we introduce KPop, a novel versatile method based on full k-mer spectra and dataset-specific transformations, through which thousands of assembled or unassembled microbial genomes can be quickly compared. Unlike MinHash-based methods t...
Comparative Study
Genome biology. 2025 Jun 18;26(1):170. DOI:10.1186/s13059-025-03585-8 2025