ArticleBioinformatics and biology insights2022
Computational Analyses Reveal Fundamental Properties of the Hemophilia Literature in the Last 6 Decades.
Article in Bioinformatics and biology insights, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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.
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.
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Who cites it
0 citing papers in PubMed, 1 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hemophilia is an inherited blood coagulation disorder caused by mutations on the coagulation factors VIII or IX genes. Although it is a relatively rare disease, the research community is actively working on this topic, producing almost 6000 manuscripts in the last 5 years. Given that the scientific literature is increasing so rapidly, even the most avid reader will find it difficult to follow it closely. In this study, we used sophisticated computational techniques to map the hemophilia literature of the last 60 years. We created a network structure to represent authorship collaborations, where the nodes are the researchers and 2 nodes are connected if they co-authored a manuscript. We accurately identified author clusters, namely, researchers who have collaborated systematically for several years, and used text mining techniques to automatically synthesize their research specialties. Overall, this study serves as a historical appreciation of the effort of thousands of hemophilia researchers and demonstrates that a computational framework is able to automatically identify collaboration networks and their research specialties. Importantly, we made all datasets and source code available for the community, and we anticipate that the methods introduced here will pave the way for the development of systems that generate compelling hypothesis based on patterns that are imperceptible to human researchers.
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Registered trials
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.