Effects of sulfate starvation on agar polysaccharides of Gracilaria species (Gracilariaceae, Rhodophyta) from Morib, Malaysia

The effects of sulfate starvation on the agar characteristics of Gracilaria species was investigated by culturing two red algae from Morib, Malaysia, Gracilaria changii and Gracilaria salicornia in sulfate-free artificial seawater for 5 days. The seaweed samples were collected in October 2012 and March 2013, periods which have significant variation in the amount of rainfall. The agar yields were shown to be independent of sulfate availability, with only 0.60–1.20 % increment in treated G. changii and 0.31–1.40 % increment in treated G. salicornia while their gel strengths did not increase significantly (approximately 5–7 %) after sulfate starvation for both species. The gelling and melting temperatures did not vary between control and treated samples from both species, except for the treated G. changii collected in March 2013. The gel syneresis index of G. salicornia collected in March 2013 increased significantly after sulfate deprivation. Sulfate starvation introduced some variations in the content of 3, 6-anhydrogalactose and total sulfate esters, but the changes did not have a pronounced effect on the physical properties of agar

Mlvis: A Web Tool For Machine Learning-Based Virtual Screening In Early-Phase Of Drug Discovery And Development

Virtual screening is an important step in early-phase of drug discovery process. Since there are thousands of compounds, this step should be both fast and effective in order to distinguish drug-like and nondrug-like molecules. Statistical machine learning methods are widely used in drug discovery studies for classification purpose. Here, we aim to develop a new tool, which can classify molecules as drug-like and nondrug-like based on various machine learning methods, including discriminant, tree-based, kernel-based, ensemble and other algorithms. To construct this tool, first, performances of twenty-three different machine learning algorithms are compared by ten different measures, then, ten best performing algorithms have been selected based on principal component and hierarchical cluster analysis results. Besides classification, this application has also ability to create heat map and dendrogram for visual inspection of the molecules through hierarchical cluster analysis. Moreover, users can connect the PubChem database to download molecular information and to create two-dimensional structures of compounds. This application is freely available through www.biosoft.hacettepe.edu.tr/MLViS/.PubMedWoSScopu