Evidence map›Paper›PMID 38361606›Full record

ArticleiScience2024

DandD: Efficient measurement of sequence growth and similarity.

Jessica K Bonnie, Omar Y Ahmed, Ben Langmead

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Elucidating Transitions ofJournal of computational biology : a journal of computational molecular cell biology · 2026
    Article
  2. Article
  3. Prokrustean Graph: A substring index for rapid k-mer size analysis.bioRxiv : the preprint server for biology · 2025
    Article
  4. Investigating DNA words and their distributions across the tree of life.Computational and structural biotechnology journal · 2025
    Article
  5. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Jessica K BonnieDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Omar Y AhmedDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.
Ben LangmeadDepartment of Computer Science, Johns Hopkins University, Baltimore, MD, USA.

Funding

Methods for sequencing data analysis and archive-scale data science - RenewalR35GM139602 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI Benjamin Thomas Langmead · 2021 to 2026
$5.0M
Personal and panel references for improved alignmentR01HG011392 · NHGRI · JOHNS HOPKINS UNIVERSITY · PI LANGMEAD, BENJAMIN THOMAS · 2020 to 2025
$4.2M
New algorithms and tools for large-scale genomic analysesR01HG012252 · NHGRI · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Aaron R Quinlan · 2022 to 2026
$3.2M
Pre-Doctoral Training Program in Computational MedicineT32GM119998 · NIGMS · JOHNS HOPKINS UNIVERSITY · PI MAC GABHANN, FEILIM C · 2017 to 2021
$1.5M
NHGRI NIH HHS R01 HG011392NHGRI NIH HHS R01 HG012252NIGMS NIH HHS R35 GM139602NIGMS NIH HHS T32 GM119998
6 · The paper itself

Abstract

Genome assembly databases are growing rapidly. The redundancy of sequence content between a new assembly and previous ones is neither conceptually nor algorithmically easy to measure. We introduce pertinent methods and DandD, a tool addressing how much new sequence is gained when a sequence collection grows. DandD can describe how much structural variation is discovered in each new human genome assembly and when discoveries will level off in the future. DandD uses a measure called δ ("delta"), developed initially for data compression and chiefly dependent on

Indexed as

Biocomputational methodGenomic analysisGenomicsSequence analysis

Identifiers

PMID38361606
PMCPMC10867639

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.