ArticleJournal of computational biology : a journal of computational molecular cell biology2018
A Flow Procedure for Linearization of Genome Sequence Graphs.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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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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Who cites it
4 citing papers in PubMed.
- Linearization of genome sequence graphs revisited.iScience · 2021Article
- A Flow Procedure for Linearization of Genome Sequence Graphs.Journal of computational biology : a journal of computational molecular cell biology · 2018Article
- Coordinate systems for supergenomes.Algorithms for molecular biology : AMB · 2018Article
- Genome graphs and the evolution of genome inference.Genome research · 2017Review
Corrections and comments
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Authors and funding
8 authors.
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Abstract
Efforts to incorporate human genetic variation into the reference human genome have converged on the idea of a graph representation of genetic variation within a species, a genome sequence graph. A sequence graph represents a set of individual haploid reference genomes as paths in a single graph. When that set of reference genomes is sufficiently diverse, the sequence graph implicitly contains all frequent human genetic variations, including translocations, inversions, deletions, and insertions. In representing a set of genomes as a sequence graph, one encounters certain challenges. One of the most important is the problem of graph linearization, essential both for efficiency of storage and access, and for natural graph visualization and compatibility with other tools. The goal of graph linearization is to order nodes of the graph in such a way that operations such as access, traversal, and visualization are as efficient and effective as possible. A new algorithm for the linearization of sequence graphs, called the flow procedure (FP), is proposed in this article. Comparative experimental evaluation of the FP against other algorithms shows that it outperforms its rivals in the metrics most relevant to sequence graphs.
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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.