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ZiF-Predict:A Web Tool for Predicting DNA-Binding Specificity in C2H2 Zinc Finger Proteins
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作者 Bhuvan Molparia Kanav Goyal +2 位作者 Anita Sarkar Sonu Kumar Durai Sundar 《Genomics, Proteomics & Bioinformatics》 SCIE CAS CSCD 2010年第2期122-126,共5页
Engineering zinc finger protein motifs for specific DNA targets in genomes is critical in the field of genome engineering. We have developed a computational method for predicting recognition helices for C2H2 zinc fing... Engineering zinc finger protein motifs for specific DNA targets in genomes is critical in the field of genome engineering. We have developed a computational method for predicting recognition helices for C2H2 zinc fingers that bind to specific target DNA sites. This prediction is based on artificial neural network using an exhaustive dataset of zinc finger proteins and their target DNA triplets. Users can select the option for two or three zinc fingers to be predicted either in a modular or synergistic fashion for the input DNA sequence. This method would be valuable for researchers interested in designing specific zinc finger transcription factors and zinc finger nucleases for several biological and biomedical applications. The web tool ZiF-Predict is available online at http://web.iitd.ac.in/-sundar/zifpredict/. 展开更多
关键词 artificial neural network C2H2 zinc fingers zif-predict
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