Evidence map›Paper›PMID 24493737›Full record

ArticleNucleic acids research2014

Improved search heuristics find 20,000 new alignments between human and mouse genomes.

Martin C Frith, Laurent Noé

Abstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  4. DomesticatingFrontiers in plant science · 2023
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  18. A coverage criterion for spaced seeds and its applications to support vector machine string kernels and k-mer distances.Journal of computational biology : a journal of computational molecular cell biology · 2014
    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

2 authors.

Martin C FrithComputational Biology Research Center, AIST, 2-4-7 Aomi, Koto-ku, Tokyo 135-0064, Japan and LIFL (UMR 8022)/INRIA Lille Nord-Europe, bat M3 Ext., Université Lille1 59655 Villeneuve d'Ascq Cedex, France.
Laurent Noé

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human-dog and melanogaster-pseudoobscura comparisons, but not for human-mouse, which suggests that we still miss many human-mouse alignments. Our optimized heuristics find ∼20,000 new human-mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.

Indexed as

Genome, HumanAnimalsDogsGenomeGenomicsHumansMiceSequence AlignmentSequence Analysis, DNA

Identifiers

PMID24493737
PMCPMC3985675

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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.