Article in Global health, epidemiology and genomics, 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.
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
21 authors.
Lyndon ZassComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0001-8862-1706
Katherine JohnstonComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0001-6688-1208
Alia BenkahlaLaboratory of BioInformatics, BioMathematics and BioStatistics LR16IPT09, Institut Pasteur de Tunis, Tunis, Tunisia.ORCID 0000-0001-9988-3250
Melek ChaouchLaboratory of BioInformatics, BioMathematics and BioStatistics LR16IPT09, Institut Pasteur de Tunis, Tunis, Tunisia.ORCID 0000-0001-5868-4204
Judit KumuthiniSouth African National Bioinformatics Institute (SANBI), Life Sciences Building, University of Western Cape, Bellville, Cape Town, South Africa.ORCID 0000-0002-8008-1917
Fouzia RadouaniChlamydiae & Mycoplasmas Laboratory Research Department, Institut Pasteur du Maroc, 20360 Casablanca, Morocco.ORCID 0000-0002-6221-2661
Liberata Alexander MwitaMuhimbili Sickle Cell Program, Department of Hematology and Blood Transfusion, Muhimbili University of Health and Allied Sciences, Dar-es-Salaam, Tanzania.ORCID 0000-0002-5693-529X
Nihad AlsayedKush Centre for Genomics & Biomedical Informatics, Biotechnology Perspectives Organization, Khartoum 11111, Sudan.ORCID 0000-0002-8462-3277
Taryn AllieComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-5072-6761
Dassen SathanSoftware Information Systems Department, FOICDT, University of Mauritius, Reduit, Mauritius.ORCID 0000-0002-0291-9964
Upendo MasamuMuhimbili Sickle Cell Program, Department of Hematology and Blood Transfusion, Muhimbili University of Health and Allied Sciences, Dar-es-Salaam, Tanzania.ORCID 0000-0002-1682-0236
Milaine Sergine Seuneu TchamgaDepartment of Mathematics and Physics, Cape Peninsula University of Technology, Bellville, Cape Town, South Africa.ORCID 0000-0002-2366-0154
Tsaone TamuhlaComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0001-5966-9153
Chaimae SamtalLaboratory of Biotechnology, Environment, Agri-Food and Health, Faculty of Sciences Dhar El Mahraz-Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco.ORCID 0000-0003-4899-7463
Victoria NembawareDivision of Human Genetics, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.ORCID 0000-0001-7966-4042
Zoe GillComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0002-5960-2941
Samah AhmedKush Centre for Genomics & Biomedical Informatics, Biotechnology Perspectives Organization, Khartoum 11111, Sudan.ORCID 0000-0002-1782-7624
Yosr HamdiLaboratory of Biomedical Genomics and Oncogenetics, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis, Tunisia.ORCID 0000-0002-2815-1834
Faisal FadlelmolaKush Centre for Genomics & Biomedical Informatics, Biotechnology Perspectives Organization, Khartoum 11111, Sudan.ORCID 0000-0001-8351-264X
Nicki TiffinComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0001-5083-2735
Nicola MulderComputational Biology Division, Department of Integrative Biomedical Sciences, IDM, University of Cape Town, Cape Town, South Africa.ORCID 0000-0003-4905-0941
Funding
H3ABioNet: informatics solutions for H3AfricaU24HG006941 · NHGRI · UNIVERSITY OF CAPE TOWN · PI MULDER, NICOLA · 2017 to 2021
$12.9M
NHGRI NIH HHS U24 HG006941
6 · The paper itself
Abstract
Modern biomedical research is characterised by its high-throughput and interdisciplinary nature. Multiproject and consortium-based collaborations requiring meaningful analysis of multiple heterogeneous phenotypic datasets have become the norm; however, such analysis remains a challenge in many regions across the world. An increasing number of data harmonisation efforts are being undertaken by multistudy collaborations through either prospective standardised phenotype data collection or retrospective phenotype harmonisation. In this regard, the Phenotype Harmonisation Working Group (PHWG) of the Human Heredity and Health in Africa (H3Africa) consortium aimed to facilitate phenotype standardisation by both promoting the use of existing data collection standards (hosted by PhenX), adapting existing data collection standards for appropriate use in low- and middle-income regions such as Africa, and developing novel data collection standards where relevant gaps were identified. Ultimately, the PHWG produced 11 data collection kits, consisting of 82 protocols, 38 of which were existing protocols, 17 were adapted, and 27 were novel protocols. The data collection kits will facilitate phenotype standardisation and harmonisation not only in Africa but also across the larger research community. In addition, the PHWG aims to feed back adapted and novel protocols to existing reference platforms such as PhenX.
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.
Developing Clinical Phenotype Data Collection Standards for Research in Africa. · full record | OpenQuestion