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Record W2780728213 · doi:10.1038/s41588-018-0262-1

Comparative genomics of the major parasitic worms

2018· article· en· W2780728213 on OpenAlexafffund
Avril Coghlan, James A. Cotton, Nancy Holroyd, Adam J. Reid, Diogo M. Ribeiro, Eleanor Stanley, Helen Beasley, Hayley M. Bennett, Stephen R. Doyle, Daria Gordon, Bhavana Harsha, Thomas Huckvale, Jane Lomax, Gabriel Rinaldi, Myriam Shafie, Alan Tracey, Matthew Berriman, Rahul Tyagi, Bruce A. Rosa, Kymberlie Hallsworth-Pepin, John Martin, Philip Ozersky, Xu Zhang, Makedonka Mitreva, Isheng Jason Tsai, Huei‐Mien Ke, Tzu‐Hao Kuo, Tracy J. Lee, Dominik R. Laetsch, Gaganjot Kaur, Georgios Koutsovoulos, Sujai Kumar, Mark Blaxter, Robin N. Beech, Tim A. Day, Nicolas J. Wheeler, Rick M. Maizels, Prudence Mutowo, Neil D. Rawlings, Kevin Howe, Andrew R. Leach, John Parkinson, Lakshmipuram S. Swapna, David W. Taylor, Mostafa Zamanian, Fiona Allan, Aidan M. Emery, Peter D. Olson, David Rollinson, Judith E. Allen, Kazuhito Asano, Simon A. Babayan, Eileen Devaney, Yvonne Harcus, Germanus S. Bah, Vincent N. Tanya, S.A. Bisset, Estela Castillo, Joseph A. Cook, Philip J. Cooper, Teresa Cruz‐Bustos, Antonio Osuna, Mercedes Gómez-Samblás, Carmen Cuéllar, Mark L. Eberhard, Keeseon S. Eom, John S. Gilleard, John M. Hawdon, Dolores E. Hill, Joseph F. Urban, Dante S. Zarlenga, Jane E. Hodgkinson, Benjamin L. Makepeace, Petr Horák, Martin Kalbe, Taisei Kikuchi, Jacqueline B. Matthews, Antonio Muro, Noel M. O’Boyle, F Partònò, Kenneth Pfarr, Pilar Foronda, Hiroshi Sato, Manuela Schnyder, Tomáš Scholz, Rafael Toledo, Lian-Chen Wang

Bibliographic record

VenueNature Genetics · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicParasite Biology and Host Interactions
Canadian institutionsUniversity of TorontoSickKids FoundationHospital for Sick ChildrenCanada Research ChairsUniversity of CalgaryMcGill University
FundersNational Institute of General Medical SciencesBiologické Centrum, Akademie Věd České RepublikyBiotechnology and Biological Sciences Research CouncilNational Institute of Allergy and Infectious DiseasesMedical Research CouncilNatural Sciences and Engineering Research Council of CanadaDirectorate for Biological SciencesNational Institutes of HealthNational Human Genome Research InstituteWellcome TrustUniversitas IndonesiaRural and Environment Science and Analytical Services DivisionScottish GovernmentUniversity of TorontoEuropean Molecular Biology LaboratoryEuropean Bioinformatics InstituteCompute CanadaJames Hutton Institute
KeywordsBiologyGenomicsGenomeComparative genomicsGene familyIn silicoPhylogeneticsGeneParasitismHost (biology)Evolutionary biologyGeneticsComputational biology

Abstract

fetched live from OpenAlex

Parasitic nematodes (roundworms) and platyhelminths (flatworms) cause debilitating chronic infections of humans and animals, decimate crop production and are a major impediment to socioeconomic development. Here we report a broad comparative study of 81 genomes of parasitic and non-parasitic worms. We have identified gene family births and hundreds of expanded gene families at key nodes in the phylogeny that are relevant to parasitism. Examples include gene families that modulate host immune responses, enable parasite migration though host tissues or allow the parasite to feed. We reveal extensive lineage-specific differences in core metabolism and protein families historically targeted for drug development. From an in silico screen, we have identified and prioritized new potential drug targets and compounds for testing. This comparative genomics resource provides a much-needed boost for the research community to understand and combat parasitic worms. Comparative study of 81 genomes of parasitic and non-parasitic worms identifies gene family births and expanded gene families at key nodes in the phylogeny that are relevant to parasitism and proteins historically targeted for drug development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.327
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations610
Published2018
Admission routes2
Has abstractyes

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