We would like to thank all the participants involved in this study, and all members of the Japan COVID-19 Task Force engaged in clinical and research work on COVID-19 every day. All members contributed cases to this study.
Kensuke Nakagawara, Hirofumi Kamata, Shotaro Chubachi, Hiromu Tanaka, Ho Lee, Shiro Otake, Takahiro Fukushima, Tatsuya Kusumoto, Atsuho Morita, Shuhei Azekawa, Mayuko Watase, Takanori Asakura, Katsunori Masaki, Makoto Ishii & Koichi FukunagaHo Namkoong & Naoki HasegawaTakanori AsakuraTakanori AsakuraMakoto Ishii, Akira Ando & Naozumi HashimotoAkifumi Endo & Ryuji Koike
Department of Emergency and Critical Care Medicine, Faculty of Medicine, Fukuoka University Hospital, Fukuoka, JapanDepartment of Internal Medicine and Rheumatology, Faculty of Medicine and Graduate School of Medicine, Juntendo University, Tokyo, JapanDepartment of Respiratory Medicine, Faculty of Medicine and Graduate School of Medicine, Juntendo University, Tokyo, JapanDepartment of Respiratory Medicine and Allergy, Tosei General Hospital, Seto, JapanYoshikazu MutohKatsushi...
Division of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, the University of Tokyo, Tokyo, JapanInstitute of Research, Tokyo Medical and Dental University, Tokyo, JapanSatoru MiyanoDivision of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
We have summarized this news so that you can read it quickly. If you are interested in the news, you can read the full text here. Read more:
Health Health Latest News, Health Health Headlines
Similar News:You can also read news stories similar to this one that we have collected from other news sources.
DGH-GO: dissecting the genetic heterogeneity of complex diseases using gene ontology - BMC BioinformaticsBackground Complex diseases such as neurodevelopmental disorders (NDDs) exhibit multiple etiologies. The multi-etiological nature of complex-diseases emerges from distinct but functionally similar group of genes. Different diseases sharing genes of such groups show related clinical outcomes that further restrict our understanding of disease mechanisms, thus, limiting the applications of personalized medicine approaches to complex genetic disorders. Results Here, we present an interactive and user-friendly application, called DGH-GO. DGH-GO allows biologists to dissect the genetic heterogeneity of complex diseases by stratifying the putative disease-causing genes into clusters that may contribute to distinct disease outcome development. It can also be used to study the shared etiology of complex-diseases. DGH-GO creates a semantic similarity matrix for the input genes by using Gene Ontology (GO). The resultant matrix can be visualized in 2D plots using different dimension reduction methods (T-SNE, Principal component analysis, umap and Principal coordinate analysis). In the next step, clusters of functionally similar genes are identified from genes functional similarities assessed through GO. This is achieved by employing four different clustering methods (K-means, Hierarchical, Fuzzy and PAM). The user may change the clustering parameters and explore their effect on stratification immediately. DGH-GO was applied to genes disrupted by rare genetic variants in Autism Spectrum Disorder (ASD) patients. The analysis confirmed the multi-etiological nature of ASD by identifying four clusters of genes that were enriched for distinct biological mechanisms and clinical outcome. In the second case study, the analysis of genes shared by different NDDs showed that genes causing multiple disorders tend to aggregate in similar clusters, indicating a possible shared etiology. Conclusion DGH-GO is a user-friendly application that allows biologists to study the multi-etiological natu
Source: BioMedCentral - 🏆 22. / 71 Read more »