Searching journal content for articles similar to Chuang et al. 13 (2): 313.

Displaying results 1-10 of 2017
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  1. ...HMM, a multivariate hidden Markov model algorithm that integrates histone mark ChIP-seq data into functional chromatin states (Ernst and Kellis 2017). Genome segmentation into six states confirmed that constitutively active ERBS were more often found in active promoters, both in E2-treated (Fig. 3D; Supplemental...
  2. ...additive and epistatic 34 effects. To bridge the gap between algorithmic advancements and biological interpretability, 35 we develop artificial intelligence genomic prediction (AIGP), an open-source end-to-end 36 toolkit for genomic prediction research. Our findings highlight the potential of ML for 37...
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  3. .... For single-cell assays, some cell types may be lost, underrepresented, or annotated incorrectly (Garmire et al. 2024). Naturally, reference and method selection are critical considerations. Without a solid understanding of biological context, users cannot assess the accuracy of algorithmic annotations...
  4. ...detection methods for individual samples, comprehensively profiling all SV types in a sample often requires integrating results from multiple bioinformatics algorithms. To address the challenges, several specialized SV merging tools have been developed to improve the analysis of complex genomic structures...
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  5. ...integrative summary of such data sets. Here, we present the ENCODE4 Catalog of Segway Annotations, a set of sample-specific -wide chromatin state annotations of 234 human biosamples inferred from 1,794 genomics experiments. This catalog identifies genomic elements, accurately captures cell type...
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  6. ...; for review, see Libbrecht et al. 2021). They take a collection of epigenomic assay data sets from a given cell type or tissue as input and partition the into segments with similar patterns in the input data sets. The output is an annotation that assigns a label to each genomic position. These algorithms use...
  7. ...visualization algorithm to project k-mers to 2D space by extending the UMAP framework. This study aims to demonstrate KMAP's utility in various biological data sets, enhancing motif discovery and sequence data exploration.Resultsk-mer manifold theory and KMAP workflowWe have built up the mathematical theories...
  8. ...studies may overlook. On the other hand, analyses of genomic variation frequently reveal a complex interplay among sequence changes, including single-nucleotide polymorphisms (SNPs) and structural variations (SVs), which are associated with altered gene expression and phenotypic traits (Collins et al...
  9. ...interactions of living organisms, and developing precise techniques to detect genomic differences between species. Nevertheless, the increase in biological data also necessitates algorithmic advances to capture the most useful information.As species evolve and diverge, they acquire new traits. This leads...
  10. ...-length transcripts. Using these technologies, researchers have reported tens of thousands of novel transcripts, even in well-annotated s, while developing new algorithms and experimental approaches to handle the noisy data. The Long-read RNA-seq Genome Annotation Assessment Project community effort benchmarked LRS...
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