Evidence map›Paper›PMID 31891531›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2020

Sparse Binary Relation Representations for Genome Graph Annotation.

Mikhail Karasikov, Harun Mustafa, Amir Joudaki, Sara Javadzadeh-No, Gunnar Rätsch, André Kahles

Abstract read
In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. BWT construction and search at the terabase scale.Bioinformatics (Oxford, England) · 2024
    Article
  5. Where the Patterns Are: Repetition-Aware Compression for Colored de Bruijn GraphsJournal of computational biology : a journal of computational molecular cell biology · 2024
    Article
  6. Article
  7. Article
  8. Fulgor: A fast and compactbioRxiv : the preprint server for biology · 2023
    Article
  9. Space-efficient representation of genomic k-mer count tables.Algorithms for molecular biology : AMB · 2022
    Article
  10. Succinct dynamic de Bruijn graphs.Bioinformatics (Oxford, England) · 2021
    Article
  11. Topology-based sparsification of graph annotations.Bioinformatics (Oxford, England) · 2021
    Article
  12. Data structures based onGenome research · 2021
    Review
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mikhail KarasikovDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.
Harun MustafaDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.
Amir JoudakiDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.
Sara Javadzadeh-NoDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.
Gunnar RätschDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.
André KahlesDepartment of Computer Science, ETH Zurich, Zurich, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

High-throughput DNA sequencing data are accumulating in public repositories, and efficient approaches for storing and indexing such data are in high demand. In recent research, several graph data structures have been proposed to represent large sets of sequencing data and to allow for efficient querying of sequences. In particular, the concept of labeled de Bruijn graphs has been explored by several groups. Although there has been good progress toward representing the sequence graph in small space, methods for storing a set of labels on top of such graphs are still not sufficiently explored. It is also currently not clear how characteristics of the input data, such as the sparsity and correlations of labels, can help to inform the choice of method to compress the graph labeling. In this study, we present a new compression approach,

Indexed as

SoftwareAlgorithmsComputational BiologyData CompressionGenomeHigh-Throughput Nucleotide SequencingHumansMolecular Sequence AnnotationSequence Analysis, DNAbinary relationscompressed data structuresgenome graph annotationsparse binary matrices

Identifiers

PMID31891531
PMCPMC7185347

What OpenQuestion holds

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Registered trials

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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.