The genomic portrait of the Picene culture provides new insights into the Italic Iron Age and the legacy of the Roman Empire in Central Italy [0.03%]
Picene文明的基因组画像揭示了意大利铁器时代的新见解以及罗马帝国在意大利中部的影响遗产
Francesco Ravasini,Helja Kabral,Anu Solnik et al.
Francesco Ravasini et al.
Background: The Italic Iron Age is characterized by the presence of various ethnic groups partially examined from a genomic perspective. To explore the evolution of Iron Age Italic populations and the genetic impact of Ro...
Marleen Balvert,Johnathan Cooper-Knock,Julian Stamp et al.
Marleen Balvert et al.
Epistasis refers to changes in the effect on phenotype of a unit of genetic information, such as a single nucleotide polymorphism or a gene, dependent on the context of other genetic units. Such interactions are both biologically plausible ...
Transcription of a centromere-enriched retroelement and local retention of its RNA are significant features of the CENP-A chromatin landscape [0.03%]
着丝粒富集的转座元件的转录及其RNA的局部滞留是CENP-A染色质景观的重要特征
B J Chabot,R Sun,A Amjad et al.
B J Chabot et al.
Background: Centromeres depend on chromatin containing the conserved histone H3 variant CENP-A for function and inheritance, while the role of centromeric DNA repeats remains unclear. Retroelements are prevalent at centro...
VI-VS: calibrated identification of feature dependencies in single-cell multiomics [0.03%]
VI-VS：单细胞多组学中特征依赖性的校准识别
Pierre Boyeau,Stephen Bates,Can Ergen et al.
Pierre Boyeau et al.
Unveiling functional relationships between various molecular cell phenotypes from data using machine learning models is a key promise of multiomics. Existing methods either use flexible but hard-to-interpret models or simpler, misspecified ...
Cohesin distribution alone predicts chromatin organization in yeast via conserved-current loop extrusion [0.03%]
仅通过保守的电流环挤压，黏着素分布即可预测酵母染色质组织
Tianyu Yuan,Hao Yan,Kevin C Li et al.
Tianyu Yuan et al.
Background: Inhomogeneous patterns of chromatin-chromatin contacts within 10-100-kb-sized regions of the genome are a generic feature of chromatin spatial organization. These features, termed topologically associating dom...
Adenine base editors induce off-target structure variations in mouse embryos and primary human T cells [0.03%]
腺嘌呤碱基编辑器在小鼠胚胎和人原代T细胞中诱发脱靶结构变异
Leilei Wu,Shutan Jiang,Meisong Shi et al.
Leilei Wu et al.
Background: The safety of CRISPR-based gene editing methods is of the utmost priority in clinical applications. Previous studies have reported that Cas9 cleavage induced frequent aneuploidy in primary human T cells, but w...
IAMSAM: image-based analysis of molecular signatures using the Segment Anything Model [0.03%]
基于Segment Anything Model的图像分子标志物分析（IAMSAM）
Dongjoo Lee,Jeongbin Park,Seungho Cook et al.
Dongjoo Lee et al.
Spatial transcriptomics is a cutting-edge technique that combines gene expression with spatial information, allowing researchers to study molecular patterns within tissue architecture. Here, we present IAMSAM, a user-friendly web-based tool...
SpottedPy quantifies relationships between spatial transcriptomic hotspots and uncovers environmental cues of epithelial-mesenchymal plasticity in breast cancer [0.03%]
SpottedPy量化空间转录组热点之间的关系，并揭示乳腺癌上皮间质可塑性的环境线索
Eloise Withnell,Maria Secrier
Eloise Withnell
Spatial transcriptomics is revolutionizing the exploration of intratissue heterogeneity in cancer, yet capturing cellular niches and their spatial relationships remains challenging. We introduce SpottedPy, a Python package designed to ident...
scDOT: optimal transport for mapping senescent cells in spatial transcriptomics [0.03%]
基于最优传输的空间转录组学中衰老细胞的映射-scDOT方法
Nam D Nguyen,Lorena Rosas,Timur Khaliullin et al.
Nam D Nguyen et al.
The low resolution of spatial transcriptomics data necessitates additional information for optimal use. We developed scDOT, which combines spatial transcriptomics and single cell RNA sequencing to improve the ability to reconstruct single c...
GraphPCA: a fast and interpretable dimension reduction algorithm for spatial transcriptomics data [0.03%]
图PCA：一种快速且可解释的空间转录组学数据降维算法
Jiyuan Yang,Lu Wang,Lin Liu et al.
Jiyuan Yang et al.
The rapid advancement of spatial transcriptomics technologies has revolutionized our understanding of cell heterogeneity and intricate spatial structures within tissues and organs. However, the high dimensionality and noise in spatial trans...