Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
0numbers the graph read from it
0cells of the map it votes in
1citing 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.
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
12 authors.
Mohaddeseh H GoudarziInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.
Samuel D RobinsonInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0002-3518-0377
Fernanda C CardosoInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.
Kushal SuryamohanResearch and Development, MedGenome Inc., Foster City, CA 94404.
Nicole LawrenceInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0002-9013-1770
David A EaglesInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.
Huy N HoangInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.
Irina VetterInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0002-3594-9588
David P FairlieInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.
Somasekar SeshagiriResearch and Development, MedGenome Inc., Foster City, CA 94404.ORCID 0000-0003-4272-6443
Glenn F KingInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0002-2308-2200
Andrew A WalkerInstitute for Molecular Bioscience, The University of Queensland, St. Lucia, QLD 4072, Australia.ORCID 0000-0003-1296-6593
Funding
Department of Education and Training | Australian Research Council (ARC) CE200100012Department of Education and Training | Australian Research Council (ARC) DP200102867Federal Government | DHAC | National Health and Medical Research Council (NHMRC) 2017461Federal Government | DHAC | National Health and Medical Research Council (NHMRC) 2035090U.S. Department of Defense (DOD) W81XWH-22-1-0219
6 · The paper itself
Abstract
Gene duplication followed by adaptation to new selection pressures has been proposed to be of central importance in the evolution of venom toxins. Coupling high-quality genome data with quantitative bioactivity readouts can be used to understand how venom toxins evolved, but such studies are rare. Here, we report a near chromosomal-level genome assembly for
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 Socratic graph.
Genome of venomous caterpillar · full record | Socratic