SEMpl: A tool for predicting consequences of SNPs in regulatory regions of genes

         SNPs(Single Nucleotide Polymorphism) have been long used to study the polymorphisms in genes of related and distant species to build their phylogeny. 88% of the disease causing SNPs reside in the non coding regions of the genomes which have so far remained to be poorly studied. Recently, Nishizaki S.S.et. al. (2020) have created a software which can predict the result of SNPs in regulatory regions of the genes. The study can prove very useful in identifying disease causing loci.

          The software has been written in C++ and is available at the following URL: https://github.com/Boyle-Lab/SEM_CPP

Reference:
Nishizaki S.S.et.al.(2020)Predicting effects of SNPs on transcription factor binding affinity. Bioinformatics 36(2):364-372.

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