iNuc-PseKNC: a sequence-based predictor for predicting nucleosome positioning in genomes with pseudo k-tuple nucleotide composition.

Motivation: Nucleosome positioning participates in many cellular activities and plays significant roles in regulating cellular processes. With the avalanche of genome sequences generated in the post-genomic age, it is highly desired to develop automated methods for rapidly and effectively identifying nucleosome positioning. Although some computational methods were proposed, most of them were species specific and neglected the intrinsic local structural properties that might play important roles in determining the nucleosome positioning on a DNA sequence.

Prediction of the types of ion channel-targeted conotoxins based on radial basis function network.

Conotoxins are small disulfide-rich peptide toxins, which have the exceptional diversity of sequences. Because conotoxins are able to specifically bind to ion channels and interfere with neurotransmission, they are considered as the excellent pharmacological candidates in drug design. Appropriate type assignment of newly sequenced mature ion channel-targeted conotoxins with computational method is conducive to explore the biological and pharmacological functions of conotoxins.

Identification of mycobacterial membrane proteins and their types using over-represented tripeptide compositions.

Mycobacterium can cause many serious diseases, such as tuberculosis and leprosy. Its membrane proteins play a critical role for multidrug-resistance and its tenacious survival ability. Knowing the types of membrane proteins will provide novel insights into understanding their functions and facilitate drug target discovery.