期刊
BIOINFORMATICS
卷 29, 期 23, 页码 3094-3096出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt518
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资金
- Science Foundation Ireland [08/IN.1/B1864, 10/RFP/GEN2749]
- Enterprise Ireland [CC20080001]
- Science Foundation Ireland (SFI) [10/RFP/GEN2749] Funding Source: Science Foundation Ireland (SFI)
Cell penetrating peptides (CPPs) are attracting much attention as a means of overcoming the inherently poor cellular uptake of various bioactive molecules. Here, we introduce CPPpred, a web server for the prediction of CPPs using a N-to-1 neural network. The server takes one or more peptide sequences, between 5 and 30 amino acids in length, as input and returns a prediction of how likely each peptide is to be cell penetrating. CPPpred was developed with redundancy reduced training and test sets, offering an advantage over the only other currently available CPP prediction method.
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