6th International Conference on Practical Applications of Computational Biology & Bioinformatics pp 121-127 | Cite as
Visual Analysis Tool in Comparative Genomics
Conference paper
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Abstract
Detecting regions with mutations associated with different pathologies is an important step in selecting relevant genes, proteins or diseases. The corresponding information of the mutations and genes is distributed in different public sources and databases, so it is necessary to use systems that can contrast different sources and select conspicuous information. This work presents a visual analysis tool that automatically selects relevant segments and the associated genes or proteins that could determine different pathologies.
Keywords
Comparative Genomic Hybridization Gain Function Detect Copy Number Variation Comparative Genomic Hybridization Microarrays Relevant Segment
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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