Cheng-Tsung Lu
According to our database1,
Cheng-Tsung Lu
authored at least 18 papers
between 2010 and 2016.
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Bibliography
2016
SOHSite: incorporating evolutionary information and physicochemical properties to identify protein <i>S</i>-sulfenylation sites.
BMC Genom., 2016
MDD-SOH: exploiting maximal dependence decomposition to identify <i>S</i>-sulfenylation sites with substrate motifs.
Bioinform., 2016
2015
A two-layered machine learning method to identify protein O-GlcNAcylation sites with O-GlcNAc transferase substrate motifs.
BMC Bioinform., December, 2015
dbSNO 2.0: a resource for exploring structural environment, functional and disease association and regulatory network of protein <i>S</i>-nitrosylation.
Nucleic Acids Res., 2015
2014
topPTM: a new module of dbPTM for identifying functional post-translational modifications in transmembrane proteins.
Nucleic Acids Res., 2014
Identification and characterization of lysine-methylated sites on histones and non-histone proteins.
Comput. Biol. Chem., 2014
Characterization and identification of protein O-GlcNAcylation sites with substrate specificity.
BMC Bioinform., 2014
RegPhos 2.0: an updated resource to explore protein kinase-substrate phosphorylation networks in mammals.
Database J. Biol. Databases Curation, 2014
2013
dbPTM 3.0: an informative resource for investigating substrate site specificity and functional association of protein post-translational modifications.
Nucleic Acids Res., 2013
ViralPhos: incorporating a recursively statistical method to predict phosphorylation sites on virus proteins.
BMC Bioinform., 2013
Proceedings of the 2013 IEEE/ACIS 12th International Conference on Computer and Information Science, 2013
2012
2011
Carboxylator: incorporating solvent-accessible surface area for identifying protein carboxylation sites.
J. Comput. Aided Mol. Des., 2011
BMC Bioinform., 2011
PlantPhos: using Maximal Dependence Decomposition to Identify Plant Phosphorylation Sites with Substrate Site Specificity.
BMC Bioinform., 2011
Exploiting maximal dependence decomposition to identify conserved motifs from a group of aligned signal sequences.
Bioinform., 2011
2010
Proceedings of the 9th IEEE/ACIS International Conference on Computer and Information Science, 2010