ArticlePLoS computational biology2015
Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints.
Article in PLoS computational biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Computational methods for predicting 3D genomic organization from high-resolution chromosome conformation capture data.Briefings in functional genomics · 2020Article
- Large-scale 3D chromatin reconstruction from chromosomal contacts.BMC genomics · 2019Article
- Tracking the evolution of 3D gene organization demonstrates its connection to phenotypic divergence.Nucleic acids research · 2017Article
- Deconvolution of Ensemble Chromatin Interaction Data Reveals the Latent Mixing Structures in Cell Subpopulations.Journal of computational biology : a journal of computational molecular cell biology · 2016Article
- 3CDB: a manually curated database of chromosome conformation capture data.Database : the journal of biological databases and curation · 2016Article
- Reconstruction of 3D genome architecture via a two-stage algorithm.BMC bioinformatics · 2015Article
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Authors and funding
2 authors.
Funding
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Abstract
The study of the 3D architecture of chromosomes has been advancing rapidly in recent years. While a number of methods for 3D reconstruction of genomic models based on Hi-C data were proposed, most of the analyses in the field have been performed on different 3D representation forms (such as graphs). Here, we reproduce most of the previous results on the 3D genomic organization of the eukaryote Saccharomyces cerevisiae using analysis of 3D reconstructions. We show that many of these results can be reproduced in sparse reconstructions, generated from a small fraction of the experimental data (5% of the data), and study the properties of such models. Finally, we propose for the first time a novel approach for improving the accuracy of 3D reconstructions by introducing additional predicted physical interactions to the model, based on orthologous interactions in an evolutionary-related organism and based on predicted functional interactions between genes. We demonstrate that this approach indeed leads to the reconstruction of improved models.
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Registered trials
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