SPalmitoylC-PseAAC: A sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-palmitoylation sites in proteins

PtdIns4P-mediated electrostatic forces influence S-acylation of peripheral proteins at the Golgi complex

“…Nevertheless, results shown in Figure 5 clearly indicate that basic amino acid residues surrounding S-acylatable cysteines are not required for the enzymatic process itself. These finding and assumptions are strongly supported by a recently developed predictor for S-Palmitoylation sites in proteins (SPalmitoylC-PseAAC) [44]. The software developers used Chou's Pseudo Amino Acid Composition (PseAAC) and relative/absolute position-based features.…”

South Atlantic Anomaly, Ionospheric Signals from Seismic Events

“…It is without exaggeration to say that the "5-steps rule" has been used at a very deeper levels of many molecular biology systems, as clearly and remarkably indicated by a series of the following reports: 1) "prediction of S-sulfenylation Sites" [2], 2) "identify phosphohistidine sites in proteins" [3], 3) "identify tyrosine sulfation sites" [4], 4) "prediction of S-sulfenylation sites" [5], 5) "exploring DNA-binding proteins" [6], 6) "reveal active compound and mechanism of shuangsheng pingfei san on idiopathic pulmonary fibrosis [7], 7) "exploring DNA-binding proteins " [6], 8) "predict splice junctions with interpretable bidirectional long short-term memory networks" [8], 9) "identify hydroxylation sites in proteins" [9], 10) "identifying S-palmitoylation sites in proteins" [10], 11) "identifying S-prenylation sites in proteins" [11], 12) "identification of piRNA and their functions [12], 13) "predicting secondary sequence information" [13], 14) "therapeutic treatment against Parkinson's disease" [14], 15) "identifying DNA N(6)-methyladenine sites in rice genome" [15] It is instructive to point out that in the systems of molecular biology there exist many multi-label ones where each of the individual constituents or samples considered may need two or more labels for distinction. For this kind of multi-label systems, two kinds of metrics are needed: one is the global set of metrics to indicate the global accuracy of the prediction method or predictor developed, while the other is the local metrics to indicate its local accuracy [35].…”

Recent Progresses for Computationally Identifying N6-methyladenosine Sites in Saccharomyces cerevisiae

“…where + represents the total number of positive samples investigated, while − + is the number of positive samplesincorrectly predicted to be of negative one; − the total number of negative samples investigated, while + − the number of the negative samples incorrectly predicted to be of positive one. The set of intuitive metrics has been concurred and applauded by a series of recent publications (see, e.g., [14, 16, 57-59, 74, 82, 87-100] [83,[101][102][103][104][105][106][107][108][109][110][111][112][113][114]). It is instructive t point out, however, either the conventional metrics [84] taken from math books or the intuitive metrics of Eq.5 are valid only for single label systems (where each of the constituent samples belong to one, and only one, attribute or class); for the multi-label systems (where a sample may simultaneously belong to several different attributes or classes) whose existence has become more frequent in system biology [6,7,29,[115][116][117][118][119][120][121][122][123][124][125][126][127][128][129][130][131][132][133][134], system medicine [135,…”