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Figure 1 | Genome Medicine

Figure 1

From: Getting personalized cancer genome analysis into the clinic: the challenges in bioinformatics

Figure 1

Scheme of a comprehensive bioinformatics pipeline to analyze personalized genomic information. The five steps in the pipeline are shown in the top row, with the main methods that have so far been developed for each step the middle and outstanding problems in the bottom row. (1) Revision of genomic information. In this rapidly developing area methods and software are continuously changing to match the improvements in sequencing technologies. (2) Analysis of the consequences of specific mutations and genomic alterations. The analysis needs go from the area of point mutation prediction in proteins to the much more challenging area of prediction of mutations in non-coding regions, including promoter regions and TF binding sites. Other genetic alterations important in cancer must also be taken into consideration, such as copy number variation, modification of splice sites and altered splicing patterns. (3) Mapping of gene/protein variants at the network level. At this point, the relationships between individual components (genes and proteins) are analyzed in terms of their involvement in gene control networks, protein interaction maps and signaling/metabolic pathways. It is clearly necessary to develop a network analysis infrastructure and analysis methods capable of extracting information from heterogeneous data sources. (4) Translation of the information into potential drugs or treatments. The pharmacogenomic analysis of the information is essential to identify potential drugs or treatments. The analysis at this level integrates genomic information with that obtained from databases linking drugs and potential targets, combining it with data on clinical trials drawn from text or web sources. Toxicogenomics information adds an interesting dimension that enables additional exploration of the data. (5) Finally, it is essential to make the information extracted by the systems accessible to the end users in adequate conditions, including geneticists, biomedical scientists and clinicians.

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