
doi: 10.1038/clpt.2012.51
pmid: 22549284
Eleven years since the initial drafts of the human genome were published, we have begun to see the first examples of the application of whole-genome sequencing to personalized diagnosis and therapeutics. The exponential decline in sequencing costs and the constant improvement in these technologies promise to further advance the use of a patient's full genetic profile in the clinic. However, realizing the potential benefit of such sequencing will require a concerted effort by science, medicine, law, and management. In this review, we discuss current approaches to decoding the 6 billion-letter genetic code of a whole genome in a clinical context, give current examples of translating this information into therapy-guiding knowledge, and list the challenges that will need to be surmounted before these powerful data can be fully exploited to forward the goals of personalized medicine.
Genome, Human, Genetic Variation, Antineoplastic Agents, DNA, Polymorphism, Single Nucleotide, Drug Therapy, Pharmacogenetics, Neoplasms, Genomic Structural Variation, Humans, Genetic Testing, Preventive Medicine, Precision Medicine, Pseudogenes, Repetitive Sequences, Nucleic Acid
Genome, Human, Genetic Variation, Antineoplastic Agents, DNA, Polymorphism, Single Nucleotide, Drug Therapy, Pharmacogenetics, Neoplasms, Genomic Structural Variation, Humans, Genetic Testing, Preventive Medicine, Precision Medicine, Pseudogenes, Repetitive Sequences, Nucleic Acid
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 36 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
