Searching journal content for articles similar to Steingruber et al. 9 (8): 751.

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  1. ...the advantages of ConvNeXt-based models in predicting high-resolution chromatin accessibility and regulatory effects of genetic variants. By combining ConvNeXt blocks as genomic feature extractors with CNNs, LSTMs, dilated CNNs, and transformers, we established a comprehensive framework of sequence...
  2. ...regulation layers and the complex mechanisms controlling cellular function.Whereas PCL-seq achieves high-resolution spatial profiling within individual ROIs, broader applications are currently constrained by technical limitations in throughput and ROI discrimination. The moderate ligation efficiency (∼60...
  3. ...features, treating them as a third dimension alongside the coordinate data (Hu et al. 2021), and refines the alignment using the ICP algorithm again. In contrast to atlas-based alignment frameworks, such as the Allen Common Coordinate Framework (CCFv3) (Wang et al. 2020b), a high-resolution 3D brain atlas...
  4. ...High resolution s of multiple Xiphophorus species provide new insights into microevolution, hybrid incompatibility, and epistasis Yuan Lu1,9, Edward Rice2,9, Kang Du1, Susanne Kneitz3, Magali Naville4, Corentin Dechaud4, Jean-Nicolas Volff4, Mikki Boswell1, William Boswell1, LaDeana Hillier5, Chad...
  5. ...spRefine denoises and imputes spatial1 transcriptomics with a reference-free framework2 powered by genomic language model3 Tianyu Liu1,2, Tinglin Huang3, Wengong Jin4,5, Tinyi Chu2, Rex4 Ying3, Hongyu Zhao1,2*5 1Interdepartmental Program in Computational Biology &6 Bioinformatics, Yale University...
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  6. ...↵Abdennur N, Mirny LA. 2020. Cooler: scalable storage for Hi-C data and other genomically labeled arrays. Bioinformatics 36: 311–316. doi:10.1093/bioinformatics/btz540 ↵Anders S, Pyl PT, Huber W. 2015. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31: 166–169. doi:10...
  7. ...by a mechanism which is not present in the HiP-HoP framework. Another possibility is that the experimental data lacks sufficient resolution to reveal these features. Many of the predicted ‘within-TAD’ interactions are present in publicly available HiChIP and ChIA-PET data which have higher resolution...
  8. ...et al. 2015) and cancer (Flavahan et al. 2016) through dysregulation of gene expression programs. The global impact of architecture on transcriptional programs in gliomas and other brain tumors has been difficult to assess because of the lack of high-resolution 3D maps for these cancers. We...
  9. ...interactions (Fig. 1D) are all part of an interwoven network “tapestry” that provides context for the regulation of gene expression, cell differentiation, and cell fate (Fig. 1). Within this framework, and as discussed below, disruption of one epigenetic thread may or may not impart rippling impacts across...
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  10. ..., requires efficient computational detection methods due to experimental limitations. Although machine learning predictors have been proposed, their performance could be enhanced through systematic optimization of feature encoding schemes. Here, we propose EnDeep4mC, a dual-adaptive framework integrating...
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