@article{open1763,
          volume = {1324},
           title = {Computer-Aided Virtual Screening and Designing of Cell-Penetrating Peptides.},
          author = {Ankur Gautam and Kumardeep Chaudhary and Rahul Kumar and G.P.S. Raghava},
       publisher = {Springer},
            year = {2015},
           pages = {59--69},
         journal = {Methods in molecular biology (Clifton, N.J.)},
        keywords = {Cell-penetrating peptides ? Drug delivery system ? Machine learning approach ? Virtual screening ? Support vector machine ? Prediction},
             url = {http://crdd.osdd.net/open/1763/},
        abstract = {Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles. Last decade has witnessed an unprecedented growth in CPP-based research, demonstrating the potential of CPPs as therapeutic candidates. In the past, many in silico algorithms have been developed for the prediction and screening of CPPs, which expedites the CPP-based research. In silico screening/prediction of CPPs followed by experimental validation seems to be a reliable, less time-consuming, and cost-effective approach. This chapter describes the prediction, screening, and designing of novel efficient CPPs using "CellPPD," an in silico tool.}
}