Illustration of the database storage.

<p>(A) NGS storage and (B) Bioinformatic result storage implementation in SHCND. Basically, a graph of UUID labeled nodes is formed. The graph structure (edges) itself is also materialized in UUID-named files containing JSON (not shown). Furthermore, the exact processing tool used to generate...

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Bibliographic Details
Main Author:	Marius Zeeb (19353559) (author)
Other Authors:	Paul Frischknecht (19353562) (author), Suraj Balakrishna (10053090) (author), Lisa Jörimann (21155951) (author), Jasmin Tschumi (21155954) (author), Levente Zsichla (21155957) (author), Sandra E. Chaudron (21155960) (author), Bashkim Jaha (21155963) (author), Kathrin Neumann (19353565) (author), Christine Leemann (214752) (author), Michael Huber (274369) (author), Karoline Leuzinger (10002074) (author), Huldrych F. Günthard (9623497) (author), Karin J. Metzner (9623494) (author), Roger D. Kouyos (9739791) (author)
Published:	2025
Subjects:	Microbiology Genetics Biotechnology Evolutionary Biology Immunology Cancer Science Policy Infectious Diseases Virology Biological Sciences not elsewhere classified together enrolled 21 sophisticated bioinformatic tools shift towards next population transmission dynamics performance computing resources first three decades data storage solutions biobank dating back addressing data management address key issues resistance associated mutations viral heritability traits several research projects time since infection processed ngs data characterizing hiv subpopulations 178 unique pwh drug resistance viral sequences viral genomics viral genome research purposes hiv research genomics research zphi ), therefore essential thereby become proviral origin preferred method molecular epidemiology last decade host diversity hiv pathogenesis generation sequencing early nineties downstream application central part accurately encapsulates
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Illustration of the database storage.

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