Computational Methods for Precision Oncology
Samenvatting
Precision medicine holds great promise for the treatment of cancer and represents a unique opportunity for accelerated development and application of novel and repurposed therapeutic approaches. Current studies and clinical trials demonstrate the benefits of genomic profiling for patients whose cancer is driven by specific, targetable alterations. However, precision oncologists continue to be challenged by the widespread heterogeneity of cancer genomes and drug responses in designing personalized treatments. Chapters provide a comprehensive overview of the computational approaches, methods, and tools that enable precision oncology, as well as related biological concepts. Covered topics include genome sequencing, the architecture of a precision oncology workflow, and introduces cutting-edge research topics in the field of precision oncology. This book is intended for computational biologists, bioinformaticians, biostatisticians and computational pathologists working in precision oncology and related fields, including cancer genomics, systems biology, and immuno-oncology.
Specificaties
Inhoudsopgave
<p>1. Design and implementation of a precision oncology workflow</p>
<p>2. An overview of cancer genome sequencing</p>
<p>3. Software infrastructures for precision medicine workflows</p>
<p>Part II: Current Computational Methods and Tools in Precision Oncology</p>
<p>4. Somatic and germline variant calling from next-generation sequencing data</p>
<p>5. Identification of copy number alterations from next-generation sequencing data</p>
<p>6. Genome-wide discovery of large-scale structural variants from next-generation sequencing data</p>
<p>7. Assessment of microsatellite instability from next-generation sequencing data</p>
<p>8. Computational approaches for the investigation of intra-tumor heterogeneity and clonal evolution from bulk sequencing data</p>
<p>9. Analysis of the transcriptome for precision oncology applications</p>
<p>10. Computational methods for drug repurposing</p>
<p>11. Pathway analysis for precision oncology applications</p>
<p>12. Identification of fusion transcripts from RNA-seq</p>
<p>13. Computational resources for the interpretation of variations in cancer</p>
<p>14. Analysis of electronic health records for precision oncology</p>
<p>15. Network approaches for precision oncology</p><p>16. Experimental validation of genomic alterations</p>
<p>Part III: Advanced Concepts - The Future of Precision Oncology</p>
<p>17. Molecular profiling of liquid biopsies for precision oncology</p>
<p>18. Artificial intelligence for precision oncology</p>
<p>19. Single-cell technologies in precision oncology</p>
<p>20. Computational approaches for precision immuno-oncology</p>
<p>21. Multi-omics profiling of the tumor microenvironment</p>
<p>22. Epigenetic and precision oncology</p>
<p>23. Next-generation knowledge bases to support precision oncology</p>