Evidence map›Paper›PMID 36695949›Full record

ArticleJournal of mathematical biology2023

The arithmetic topology of genetic alignments.

Christopher Barrett, Andrei Bura, Qijun He, Fenix Huang, Christian Reidys

Abstract read
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Article in Journal of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Christopher Barrett *Biocomplexity Institute, University of Virginia, 994 Research Park Boulevard, Charlottesville, VA, 22911, USA.
Andrei Bura *Biocomplexity Institute, University of Virginia, 994 Research Park Boulevard, Charlottesville, VA, 22911, USA.
Qijun He *Biocomplexity Institute, University of Virginia, 994 Research Park Boulevard, Charlottesville, VA, 22911, USA.
Fenix Huang *Biocomplexity Institute, University of Virginia, 994 Research Park Boulevard, Charlottesville, VA, 22911, USA.
Christian Reidys *Biocomplexity Institute, University of Virginia, 994 Research Park Boulevard, Charlottesville, VA, 22911, USA. cmr3hk@virginia.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a novel mathematical paradigm for the study of genetic variation in sequence alignments. This framework originates from extending the notion of pairwise relations, upon which current analysis is based on, to k-ary dissimilarity. This dissimilarity naturally leads to a generalization of simplicial complexes by endowing simplices with weights, compatible with the boundary operator. We introduce the notion of k-stances and dissimilarity complex, the former encapsulating arithmetic as well as topological structure expressing these k-ary relations. We study basic mathematical properties of dissimilarity complexes and show how this approach captures watershed moments of viral dynamics in the context of SARS-CoV-2 and H1N1 flu genomic data.

Indexed as

COVID-19Influenza A Virus, H1N1 SubtypeHumansSARS-CoV-2Sequence AlignmentHamming distancek-StancesPhylogenySequence dissimilarityWeighted algebraic homologyWeighted simplicial complexes

Identifiers

PMID36695949
PMCPMC9875784

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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.