bi-profile bayes feature extraction. PLoS One 4
(3):e4920- Lee TY, Chen SA, Hung HY, YY O (2011)
Incorporating distant sequence features and
radial basis function networks to identify ubi-
quitin conjugation sites. PLoS One 6(3):
e17331 - Hsu BK et al (2012) Incorporating evolution-
ary information and functional domains for
identifying RNA splicing factors in humans.
PLoS One 6(11):e27567 - Xie D et al (2005) LOCSVMPSI: a web server
for subcellular localization of eukaryotic pro-
teins using SVM and profile of PSI-BLAST.
Nucleic Acids Res 33(Web Server
issue):105–110 - Jones DT (1999) Protein secondary structure
prediction based on position-specific scoring
matrices. J Mol Biol 292(2):195 - Altschul SF et al (1997) Gapped BLAST and
PSI-BLAST: a new generation of protein data-
base search programs. Nucleic Acids Res 25
(17):3389–3402 - Andersen MT, Packer NH (2014) Advances in
LC–MS/MS-based glycoproteomics: getting
closer to system-wide site-specific mapping of
the N- and O-glycoproteome. Biochim Bio-
phys Acta 1844:1437–1452 - Mcguffin LJ, Bryson K, Jones DT (2000) The
PSIPRED protein structure prediction server.
Bioinformatics 16(4):404 - Ward JJ et al (2004) Prediction and functional
analysis of native disorder in proteins from the
three kingdoms of life. J Mol Biol 337(3):635 - Ahmad S, Gromiha MM, Sarai A (2003)
RVP-net: online prediction of real valued
accessible surface area of proteins from single
sequences. Bioinformatics 19(14):1849–1851 - Ahmad S, Gromiha MM, Sarai A (2003) Real
value prediction of solvent accessibility from
amino acid sequence. Proteins 50(4):629–635
42. Kenney JF, Mosak JL (1951), Mathematics of
Statistics, Van Nostrand, Princeton, NJ, 2nd
edn, pp. 36–41
43. Kawashima S et al (2008) AAindex: amino acid
index database, progress report 2008. Nucleic
Acids Res 36(Database issue):202–205
44. Tung CW, Ho SY (2008) Computational iden-
tification of ubiquitylation sites from protein
sequences. BMC Bioinformatics 9:310
45. Cao DS, QS X, Liang YZ (2013) Propy: a tool
to generate various modes of Chou’s PseAAC.
Bioinformatics 29:960–962
46. Du P, Gu S, Jiao Y (2014) PseAAC-General:
fast building various modes of general form of
Chou’s pseudo-amino acid composition for
large-scale protein datasets. Int J Mol Sci 15
(3):3495–3506
47. Qiu WR, Xiao X, Lin WZ (2014) iMethyl-
PseAAC: identification of protein methylation
sites via a pseudo amino acid composition
approach. Biomed Res Int 2014(12):947416
48. Zhang Y, Liu B, Dong Q, Jin VX (2011) An
improved profile-level domain linker propen-
sity index for protein domain boundary predic-
tion. Protein Pept Lett 18(1):7–16
49. Shao J et al (2012) Systematic analysis of
human lysine acetylation proteins and accurate
prediction of human lysine acetylation through
bi-relative adapted binomial score Bayes feature
representation. Mol Biosyst 8(11):2964–2973
50. Wee LJ et al (2010) SVM-based prediction of
linear B-cell epitopes using Bayes feature
extraction. BMC Genomics 11(4):S21
51. Song L et al (2014) nDNA-prot: identification
of DNA-binding proteins based on unbalanced
classification. BMC Bioinformatics 15:298
52. Li DP, Ju Y, Zou Q (2016) Protein folds pre-
diction with hierarchical structured SVM. Curr
Proteomics 13:79–85
53. Schwartz D (2012) Prediction of lysine post-
translational modifications using bioinformatic
tools. Essays Biochem 52:165–177
246 Cangzhi Jia and Yun Zuo