ArticleComputational and structural biotechnology journal2024
ppHiC: Interactive exploration of Hi-C results on the ProteinPaint web portal.
Article in Computational and structural biotechnology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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11 authors.
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Abstract
The ProteinPaint Hi-C tool (ppHiC) facilitates web-based visualization and collaborative exploration of Hi-C data, a vital resource for understanding three-dimensional genomic structures. ppHiC allows researchers to easily analyze large Hi-C datasets on a web browser without requiring the computational expertise that has heretofore limited access to this complex genomic data. The platform is compatible with multiple Hi-C data versions and boasts a highly customizable interface, including a configuration panel for the precise adjustment of key visualization parameters. The tool's interactive features offer a broad range of views, from whole-genome landscapes to detailed interactions between pairs of loci, that are accessible within a single, integrated environment. Here, we demonstrate how using ppHiC to visualize an altered chromatin conformational landscape in neuroblastoma can inform understanding of the genomic rearrangements in this cancer.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.