A dynamic regulome of shoot-apical-meristem-related homeobox transcription factors modulates plant architecture in maize [0.03%]
玉米节间长度和株型的调控网络分析揭示SHRT是控制株高的新基因
Zi Luo,Leiming Wu,Xinxin Miao et al.
Zi Luo et al.
Background: The shoot apical meristem (SAM), from which all above-ground tissues of plants are derived, is critical to plant morphology and development. In maize (Zea mays), loss-of-function mutant studies have identified...
Recruitment of the m6A/m6Am demethylase FTO to target RNAs by the telomeric zinc finger protein ZBTB48 [0.03%]
招募m6A / m6Am去甲基化酶FTO的端粒锌指蛋白ZBTB48目标RNA
Syed Nabeel-Shah,Shuye Pu,Giovanni L Burke et al.
Syed Nabeel-Shah et al.
Background: N6-methyladenosine (m6A), the most abundant internal modification on eukaryotic mRNA, and N6, 2'-O-dimethyladenosine (m6Am), are epitranscriptomic marks that function in multiple aspects of posttranscriptional...
ESCHR: a hyperparameter-randomized ensemble approach for robust clustering across diverse datasets [0.03%]
ESCHR：一种鲁棒的跨数据集聚类的超参数随机化集成方法
Sarah M Goggin,Eli R Zunder
Sarah M Goggin
Clustering is widely used for single-cell analysis, but current methods are limited in accuracy, robustness, ease of use, and interpretability. To address these limitations, we developed an ensemble clustering method that outperforms other ...
Yueqi Tao,Wenfei Xian,Zhigui Bao et al.
Yueqi Tao et al.
Background: Telomeric repeat arrays at the ends of chromosomes are highly dynamic in composition, but their repetitive nature and technological limitations have made it difficult to assess their true variation in genome d...
Splam: a deep-learning-based splice site predictor that improves spliced alignments [0.03%]
基于深度学习的剪接位点预测工具splam及其在提高拼接一致性中的应用研究
Kuan-Hao Chao,Alan Mao,Steven L Salzberg et al.
Kuan-Hao Chao et al.
The process of splicing messenger RNA to remove introns plays a central role in creating genes and gene variants. We describe Splam, a novel method for predicting splice junctions in DNA using deep residual convolutional neural networks. Un...
Dimension reduction, cell clustering, and cell-cell communication inference for single-cell transcriptomics with DcjComm [0.03%]
DcjComm：单细胞转录组的维度降低、细胞聚类和细胞间通讯推断方法
Qian Ding,Wenyi Yang,Guangfu Xue et al.
Qian Ding et al.
Advances in single-cell transcriptomics provide an unprecedented opportunity to explore complex biological processes. However, computational methods for analyzing single-cell transcriptomics still have room for improvement especially in dim...
Kirsten Seale,Andrew Teschendorff,Alexander P Reiner et al.
Kirsten Seale et al.
Background: During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated p...
DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates [0.03%]
深度生成模型估计单细胞RNA剪接和降解速率
Chikara Mizukoshi,Yasuhiro Kojima,Satoshi Nomura et al.
Chikara Mizukoshi et al.
Messenger RNA splicing and degradation are critical for gene expression regulation, the abnormality of which leads to diseases. Previous methods for estimating kinetic rates have limitations, assuming uniform rates across cells. DeepKINET i...
Publisher Correction: scParser: sparse representation learning for scalable single-cell RNA sequencing data analysis [0.03%]
出版致谢：scParser：用于大规模单细胞RNA测序数据分析的稀疏表示学习
Kai Zhao,Hon-Cheong So,Zhixiang Lin
Kai Zhao
Published Erratum
Genome biology. 2024 Sep 4;25(1):238. DOI:10.1186/s13059-024-03378-5 2024
Author Correction: A benchmark of computational methods for correcting biases of established and unknown origin in CRISPR-Cas9 screening data [0.03%]
作者勘误：建立并纠正CRISPR-Cas9筛查数据已知和未知偏差的计算方法基准测试
Alessandro Vinceti,Rafaele M Iannuzzi,Isabella Boyle et al.
Alessandro Vinceti et al.
Published Erratum
Genome biology. 2024 Sep 4;25(1):239. DOI:10.1186/s13059-024-03387-4 2024