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In the previous studies, the prediction of phosphorylation sites was mainly based on sequence features.
A molecular phylogenetic analysis procedure based on sequence features is initiated by gathering a set of sequences derived from a common origin.
Disordered regions can be classified into three groups based on sequence features alone, where proteins from each group are identified by different experimental techniques [9].
Some applications classify genes based on sequence features [12], or use protein-protein interaction networks [9], [13] while others (GeneSeeker, SUSPECTS) combine different approaches.
Based on sequence features, CtCP1 belongs to Epl1 cluster of CP proteins [ 35].
T. H. Zhao et al. proposed a new method to predict protein disordered regions based on sequence features.
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Hence, developing a reliable in silico sumoylation prediction method that has a better accuracy based on sequence derived features, bears a significant importance for the understanding complex diseases, cellular processes and epigenetic mechanisms.
Based on sequence and structural features, snoRNAs can be classified into two families-box C/D snoRNAs and box H/ACA snoRNAs-which guide site-specific 2'-O-ribose methylation and pseudouridylation of rRNA, respectively [ 20, 21].
Here, we applied a similarity network-based methodology for the representation and analysis of protein sequences and structures sets using a non-redundant set of 311 proteins and three different information criteria based on sequence-derived features, sequence local alignment and structural alignment.
Predictions are based on sequence-derived features.
The protein representation used in the binary classifiers is based on sequence-derived features (e.g. amino acid composition) and gene ontology (GO) terms.
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based on bioprocess features
based on sequence networks
based on chemical features
based on sequence alignments
based on extracting features
based on location features
based on color features
based on land features
based on clique features
based on dialogue features
based on edge features
based on texture features
based on image features
based on melanoma features
based on sequence polymorphisms
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