Integrative bioinformatics for biomedical big data a no-boundary thinking approach
The volume and complexity of biological and biomedical research continues to grow exponentially with cutting-edge technologies such as high-throughput sequencing. Unfortunately, bioinformatics analysis is often considered only after data have been generated, which significantly limits the ability to...
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2023
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| 520 | |a The volume and complexity of biological and biomedical research continues to grow exponentially with cutting-edge technologies such as high-throughput sequencing. Unfortunately, bioinformatics analysis is often considered only after data have been generated, which significantly limits the ability to make sense of complex big data. This unique book introduces the idea of No-Boundary Thinking (NBT) in biological and biomedical research, which aims to access, integrate, and synthesize data, information, and knowledge from bioinformatics to define important problems and articulate impactful research questions. This interdisciplinary volume brings together a team of bioinformatics specialists who draw on their own experiences with NBT to illustrate the importance of collaborative science. It will help stimulate discussion and application of NBT, and will appeal to all biomedical researchers looking to maximize their use of bioinformatics for making scientific discoveries. | ||
| 700 | 1 | |a Huang, Xiuzhen | |
| 700 | 1 | |a Moore, Jason H. | |
| 700 | 1 | |a Zhang, Yu | |
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| id | ZDB-20-CTM-CR9781316335208 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-18T12:04:26Z |
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| isbn | 9781316335208 |
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| spelling | Integrative bioinformatics for biomedical big data a no-boundary thinking approach edited by Xiuzhen Huang, Jason H. Moore, Yu Zhang Cambridge Cambridge University Press 2023 1 Online-Ressource (x, 171 Seiten) txt c cr The volume and complexity of biological and biomedical research continues to grow exponentially with cutting-edge technologies such as high-throughput sequencing. Unfortunately, bioinformatics analysis is often considered only after data have been generated, which significantly limits the ability to make sense of complex big data. This unique book introduces the idea of No-Boundary Thinking (NBT) in biological and biomedical research, which aims to access, integrate, and synthesize data, information, and knowledge from bioinformatics to define important problems and articulate impactful research questions. This interdisciplinary volume brings together a team of bioinformatics specialists who draw on their own experiences with NBT to illustrate the importance of collaborative science. It will help stimulate discussion and application of NBT, and will appeal to all biomedical researchers looking to maximize their use of bioinformatics for making scientific discoveries. Huang, Xiuzhen Moore, Jason H. Zhang, Yu Erscheint auch als Druck-Ausgabe 9781107114302 TUM01 ZDB-20-CTM TUM_PDA_CTM https://doi.org/10.1017/9781316335208 Volltext |
| spellingShingle | Integrative bioinformatics for biomedical big data a no-boundary thinking approach |
| title | Integrative bioinformatics for biomedical big data a no-boundary thinking approach |
| title_auth | Integrative bioinformatics for biomedical big data a no-boundary thinking approach |
| title_exact_search | Integrative bioinformatics for biomedical big data a no-boundary thinking approach |
| title_full | Integrative bioinformatics for biomedical big data a no-boundary thinking approach edited by Xiuzhen Huang, Jason H. Moore, Yu Zhang |
| title_fullStr | Integrative bioinformatics for biomedical big data a no-boundary thinking approach edited by Xiuzhen Huang, Jason H. Moore, Yu Zhang |
| title_full_unstemmed | Integrative bioinformatics for biomedical big data a no-boundary thinking approach edited by Xiuzhen Huang, Jason H. Moore, Yu Zhang |
| title_short | Integrative bioinformatics for biomedical big data |
| title_sort | integrative bioinformatics for biomedical big data a no boundary thinking approach |
| title_sub | a no-boundary thinking approach |
| url | https://doi.org/10.1017/9781316335208 |
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