Abstract
High-throughput technologies have been utilized extensively in life science due to their ability to generate and analyze large datasets, which has revolutionized research methodologies and enabled scientists to explore and understand biological systems at unprecedented levels of detail. These technologies aid in identifying and comprehending human disorders in terms of genomics and proteomics by utilizing the rapidly expanding field of bioinformatics, which analyzes large amounts of biological data, combining biology, statistics, and computer science. To construct a hypothetical phenomenon in drug research and discovery, several computational models aid in understanding and predicting disease states, development, screens, and photography circumstances. This chapter covers the many models and platforms using sophisticated technology for genetic diseases or conditions. Lastly, clarify by going over developmental areas and using a case study.
| Original language | English |
|---|---|
| Title of host publication | Deep Learning in Genetics and Genomics |
| Subtitle of host publication | Volume 1: Foundations and Introductory Applications |
| Publisher | Elsevier |
| Pages | 59-75 |
| Number of pages | 17 |
| ISBN (Electronic) | 9780443275746 |
| ISBN (Print) | 9780443275753 |
| DOIs | |
| State | Published - 1 Jan 2024 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Bioinformatics
- Cancer
- Computational tools
- Genomics
- Proteomics
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