LEADER 02382nam 2200361 450 001 9910597905503321 005 20230329072337.0 035 $a(CKB)4920000000095125 035 $a(NjHacI)994920000000095125 035 $a(EXLCZ)994920000000095125 100 $a20230329d2018 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aSpecial Protein Molecules Computational Identification /$fedited by Quan Zou 210 1$aBasel, Switzerland :$cMDPI - Multidisciplinary Digital Publishing Institute,$d2018. 215 $a1 online resource (308 pages) 311 $a3-03897-043-3 330 $aIt is time consuming and costly to detect new molecules of some special proteins. These special proteins include cytokines, enzymes, cell-penetrating peptides, anticancer peptides, cancer lectins, G-protein-coupled receptors, etc. Researchers often employ computer programs to list some candidates, and to validate the candidates with molecular experiments. These computer programs are key to possible savings on wet experiment costs. Software results with high false positive will lead to high costs in the validation process. In this Special Issue, we focus on these computer program approaches and algorithms. Some "golden features" from protein primary sequences have been proposed for these problems, such as Chou's PseAAC (pseudo amino acid composition). PseAAC has been tried on nearly all kinds of protein identification, together with SVM (support vector machines, a type of classifier). However, I prefer special features, and classification methods should be proposed for special protein molecules. "Golden features" cannot work well on all kinds of proteins. I hope that submissions will focus on a type of special protein molecule, collect related data sets, obtain better prediction performance (especially low false positives), and develop user-friendly software tools or web servers. 606 $aComputational chemistry$vPeriodicals 606 $aProteins 615 0$aComputational chemistry 615 0$aProteins. 676 $a547.75 702 $aZou$b Quan 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910597905503321 996 $aSpecial Protein Molecules Computational Identification$92929134 997 $aUNINA