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New computational tool improves gene identification

Like finding a needle in a haystack, identifying genes that are involved in particular diseases can be an arduous and time consuming process. Looking to improve this process, a team led by researchers at Baylor College of Medicine has developed a new bioinformatics tool that analyzes CRISPR pooled screen data and identifies candidates for potentially relevant genes with greater sensitivity and accuracy than other existing methods. The new analytical web-based tool also is quicker and more user friendly as it does not require bioinformatics training to use it.

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Thursday, May 9, 2019