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Data science for genomics /
Data Science for Genomics presents the foundational concepts of data science as they pertain to genomics, encompassing the process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions and supporting decision-making. Sections...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Amsterdam :
Academic Press,
2022.
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| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- 1. Introduction to Data Science<br>2. Toolboxes for Data Scientists<br>3. Machine Learning and Deep Learning: A Concise Overview<br>4. Artificial Intelligence<br>5. Data Privacy and Data Trust<br>6. Visual Data Analysis and Complex Data Analysis<br>7. Big Data programming with Apache Spark and Hadoop<br>8. Information Retrieval and Recommender Systems<br>9. Statistical Natural Language Processing for Sentiment Analysis<br>10. Parallel Computing and High-Performance Computing<br>11. Data Science, Genomics, Genomes, and Genetics<br>12. Blockchain Technology for securing Genomic data<br>13. Cloud, edge, fog, etc., for communicating and storing data for Genome<br>14. Open Issues, Challenges and Future Research Directions towards Data science and Genomics<br>15. Privacy Laws<br>16. Ethical Concerns<br>17. Self-study questions<br>18. Problem-based learning<br>19. Key Terms/ Glossary<br>20. Appendix
- Keeping up to Date<br>21. Bibliography