dc.contributor.author | Karakoyun H.K. | |
dc.contributor.author | Sayar C. | |
dc.contributor.author | Yararbaş K. | |
dc.date.accessioned | 2024-02-04T13:30:06Z | |
dc.date.available | 2024-02-04T13:30:06Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 25901230 | |
dc.identifier.uri | https://doi.org/10.1016/j.rineng.2023.101421 | |
dc.identifier.uri | http://hdl.handle.net/11446/4845 | |
dc.description.abstract | Next-generation sequencing (NGS) technologies have completely changed the field of genomics by making it possible to rapidly and inexpensively produce genome-scale sequence data with higher precision and resolution. In recent years, rapid technological advancements driven by companies and academic institutions have expanded the range of NGS applications, from research to the clinic. Latest scientific developments have highlighted the effects of NGS technology on complex and Mendelian diseases, particularly cancer. However, the rapid adoption of NGS poses significant challenges in data processing, storage, management, and interpretation, as well as sequencing quality control, making it challenging to integrate the sequence data into clinical practice. Here, we first outline the technical features and performance of the most recent NGS platforms. Furthermore, we summarize the applications of NGS technologies in clinical diagnostics, data interpretation, and valuable bioinformatic tools and databases for analysis. Common issues in NGS processes are also discussed. © 2023 The Authors | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Elsevier B.V. | en_US |
dc.relation.ispartof | Results in Engineering | en_US |
dc.identifier.doi | 10.1016/j.rineng.2023.101421 | |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Bioinformatic tools | en_US |
dc.subject | Clinical application | en_US |
dc.subject | Databases | en_US |
dc.subject | In silico predictive tools | en_US |
dc.subject | NGS technologies | en_US |
dc.subject | Bioinformatics | en_US |
dc.subject | Data handling | en_US |
dc.subject | Diagnosis | en_US |
dc.subject | Digital storage | en_US |
dc.subject | Genome | en_US |
dc.subject | Information management | en_US |
dc.subject | Advantages and pitfalls | en_US |
dc.subject | Bioinformatic tools | en_US |
dc.subject | Clinical application | en_US |
dc.subject | Data interpretation | en_US |
dc.subject | In silico predictive tool | en_US |
dc.subject | In-silico | en_US |
dc.subject | Next-generation sequencing | en_US |
dc.subject | Next-generation sequencing technology | en_US |
dc.subject | Predictive tools | en_US |
dc.subject | Sequence data | en_US |
dc.subject | Quality control | en_US |
dc.title | Challenges in clinical interpretation of next-generation sequencing data: Advantages and Pitfalls | en_US |
dc.type | article | en_US |
dc.department | DBÜ | en_US |
dc.identifier.volume | 20 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.department-temp | Karakoyun, H.K., Biochemistry and Molecular Biology PhD Program, Institute of Health Sciences, Acıbadem Mehmet Ali Aydınlar University, Istanbul, Turkey, Sapiens Genetics Diagnostic Center, Istanbul, Turkey; Sayar, C., Sapiens Genetics Diagnostic Center, Istanbul, Turkey; Yararbaş, K., Sapiens Genetics Diagnostic Center, Istanbul, Turkey, Department of Medical Genetics, Faculty of Medicine, TC Demiroğlu Bilim University, Istanbul, Turkey | en_US |
dc.identifier.scopus | 2-s2.0-85171628570 | en_US |
dc.authorscopusid | 57441230300 | |
dc.authorscopusid | 57441230200 | |
dc.authorscopusid | 34468021600 | |