Article in Frontiers in genetics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 28% of its field
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
2 citing papers in PubMed, 3 citations in OpenAlex.
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 at 1 institution in 1 country.
Yanfei WangCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Jacqueline ChyrCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Pora KimCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Weiling ZhaoCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
Xiaobo ZhouCenter for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, United States.
The University of Texas Health Science Center at Houston · US
Funding
Systems Modeling Guided Bone regenerationU01AR069395 · NIAMS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI YANG, YUNZHI, ZHOU, XIAOBO · 2016 to 2021
$3.4M
A Novel Informatics System For Craniosynostosis SurgeryR01DE027027 · NIDCR · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2017 to 2021
$2.2M
Tissue Engineering Approaches for Improved Treatment of Early Stage Osteonecrosis of the HipR01AR072613 · NIAMS · STANFORD UNIVERSITY · PI GOODMAN, STUART B, YANG, YUNZHI · 2018 to 2022
$2.2M
Functional annotation of new genes aided by deep learningR35GM138184 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI KIM, PORA · 2020 to 2024
$1.7M
Integrative approach to studying LncRNA functionsR01GM123037 · NIGMS · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · PI ZHOU, XIAOBO · 2017 to 2020
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.
Phenotype-Genotype analysis of caucasian patients with high risk of osteoarthritis. · full record | OpenQuestion