In one paragraphArticle in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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 registryThe 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 literatureWho cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
4 · The recordCorrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
5 · Who and what moneyAuthors and funding
13 authors.
Nicole DeBruyneCenter for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Elizabeth M McCormickMitochondrial Medicine Frontier Program, Division of Human Genetics, Department of Pediatrics, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Matthew T SullenbergerCenter for Computational and Genomic Medicine, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
Funding
Pilot and Feasibility CoreU54NS115198 · NINDS · MAYO CLINIC ROCHESTER · PI MORAVA-KOZICZ, EVA · 2019 to 2023
$8.2MMitochondrial respiratory chain disease mechanistic and therapeutic modelingR35GM134863 · NIGMS · CHILDREN'S HOSP OF PHILADELPHIA · PI MARNI J FALK · 2020 to 2026
$4.3MTargeting alternative isoform variation for TCR discovery in platinum-resistant ovarian cancerR01CA287673 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Sanaz Memarzadeh, Yi Xing · 2024 to 2026
$2.1MComprehensive identification and functional study of Esrp-regulated isoforms during epithelial-mesenchymal transition.R01HD114705 · NICHD · CHILDREN'S HOSP OF PHILADELPHIA · PI Eric Chien-Wei Liao, Yi Xing · 2025 to 2026
$1.5MLong-read strategies for elucidating transcriptome complexity and advancing genomic medicineR35GM158057 · NIGMS · CHILDREN'S HOSP OF PHILADELPHIA · PI Lan Lin · 2025 to 2026
$890kComputational tools and resources to study alternative splicing and mRNA isoform variationR56HG012310 · NHGRI · CHILDREN'S HOSP OF PHILADELPHIA · PI XING, YI · 2022 to 2022
$569kU.S. Department of Health & Human Services | National Institutes of Health (NIH) R01CA287673U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01HD114705U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35GM134863U.S. Department of Health & Human Services | National Institutes of Health (NIH) R35GM158057U.S. Department of Health & Human Services | National Institutes of Health (NIH) R56HG012310U.S. Department of Health & Human Services | National Institutes of Health (NIH) U54NS115198
6 · The paper itselfAbstract
Accurate variant detection using nanopore long-read transcriptome data remains challenging. Here we present NanoTS-a deep learning-based tool for single nucleotide polymorphism detection from diverse types of nanopore transcriptome sequencing data. NanoTS outperforms existing methods, achieving F
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