Evidence map›Paper›PMID 36125448›Full record

ArticleJournal of computational biology : a journal of computational molecular cell biology2023

virDTL: Viral Recombination Analysis Through Phylogenetic Reconciliation and Its Application to Sarbecoviruses and SARS-CoV-2.

Sumaira Zaman, Samuel Sledzieski, Bonnie Berger, Yi-Chieh Wu, Mukul S Bansal

Abstract read
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In one paragraph

Article in Journal of computational biology : a journal of computational molecular cell biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Sumaira ZamanDepartment of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA.
Samuel SledzieskiComputer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Bonnie BergerComputer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
Yi-Chieh WuDepartment of Computer Science, Harvey Mudd College, Claremont, California, USA.
Mukul S BansalDepartment of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA.ORCID 0000-0003-0039-2596

Funding

Structure-Based Prediction of the InteractomeR01GM081871 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2008 to 2020
$4.3M
Manifold representations and active learning for 21 st century biologyR35GM141861 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI BERGER, BONNIE · 2021 to 2025
$1.9M
NIGMS NIH HHS R01 GM081871NIGMS NIH HHS R35 GM141861
6 · The paper itself

Abstract

An accurate understanding of the evolutionary history of rapidly-evolving viruses like SARS-CoV-2, responsible for the COVID-19 pandemic, is crucial to tracking and preventing the spread of emerging pathogens. However, viruses undergo frequent recombination, which makes it difficult to trace their evolutionary history using traditional phylogenetic methods. In this study, we present a phylogenetic workflow, virDTL, for analyzing viral evolution in the presence of recombination. Our approach leverages reconciliation methods developed for inferring horizontal gene transfer in prokaryotes and, compared to existing tools, is uniquely able to identify ancestral recombinations while accounting for several sources of inference uncertainty, including in the construction of a strain tree, estimation and rooting of gene family trees, and reconciliation itself. We apply this workflow to the

Indexed as

ChiropteraCOVID-19Severe acute respiratory syndrome-related coronavirusAnimalsEvolution, MolecularGene Transfer, HorizontalGenome, ViralHumansPandemicsPhylogenySARS-CoV-2phylogenetic reconciliationSarbecovirus evolutionSARS-CoV-2viral recombination

Identifiers

PMID36125448
PMCPMC10081712

What OpenQuestion holds

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LicenceCC BY-NC
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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.