This study concerns an attempt to establish a new method for predicting antimicrobial peptides (AMPs) which are important to the immune system. Recently, researchers are interested in designing alternative drugs based on AMPs because they have found that a large number of bacterial strains have become resistant to available antibiotics. However, researchers have encountered obstacles in the AMPs designing process as experiments to extract AMPs from protein sequences are costly and require a long set-up time. Therefore, a computational tool for AMPs prediction is needed to resolve this problem. In this study, an integrated algorithm is newly introduced to predict AMPs by integrating sequence alignment and support vector machine- (SVM-) LZ complexity pairwise algorithm. It was observed that, when all sequences in the training set are used, the sensitivity of the proposed algorithm is 95.28% in jackknife test and 87.59% in independent test, while the sensitivity obtained for jackknife test and independent test is 88.74% and 78.70%, respectively, when only the sequences that has less than 70% similarity are used. Applying the proposed algorithm may allow researchers to effectively predict AMPs from unknown protein peptide sequences with higher sensitivity.
Surveys on amphibian species in Ulu Paip Recreational Forest, Kedah were carried out over 12 consecutive months from January 2011 to December 2011. Twenty species of frogs from 11 genera and six families were recorded to inhabit this forest. This study represents the first report of amphibian species from Ulu Paip Recreational Forest.
The four-lined tree frog, Polypedates leucomystax, spawns its eggs in a moist structure called a foam nest. Four foam nests constructed by this species were collected from the Sungai Sedim Recreational Forest, Kedah, Peninsular Malaysia. Two foam nests were found deposited on the leaves of low vegetation hanging over a rock pool. One was attached inside a water tank, and one was found on grass near an ephemeral puddle. In the laboratory, the foam nests were freeze-dried and the protein concentrations quantified, fractionated, and analyzed using LC-MS/MS. Twenty-two
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.