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Current Biofuels Policies Unethical.

China Pioneers International R&D Center for Global Health.

TCM Faces Departure From EU Market.

Institut Pasteur Shanghai Creates Global Biotech Accelerator Advance BioChina.

VCs Shift from Biotech to Social Networking.

Beike, ThermoGenesis Enter Agreement on Stem Cell Therapies.

Glenmark Arm Discovers Molecule to Treat Blood Cancer.

Fortis, TotipotentRX to Set Up Stem Cell Centres.

Dr Reddy's Laboratories Expands Technology Centre in UK.

Sun Pharma, Merck in JV to Develop Generics.

SINGAPORE – A New Way of Looking at Cancer

SINGAPORE – Novel Discovery by NUS Scientists Improves Profiling of AML Patients for Targeted Therapies

SINGAPORE – Red Meat Consumption Linked with Increased Risk of Developing Kidney Failure

SINGAPORE – Thomson Medical and UK-based Cell Therapy Limited Collaborate on Stem Cell Research to Develop Regenerative Medicines

UNITED STATES – New Biomaterial Developed for Injectable Neuronal Control

UNITED STATES – Research Shines Light on Lesser Known Form of Vitamin D in Foods

UNITED STATES – MRIGlobal to Lead International Research Collaboration for Tularemia Vaccine

INDIA – Improving Agricultural Yield and Quality through Tissue Culture Technology

TAIWAN – A Cascade of Protein Aggregation Bombards Mitochondria for Neurodegeneration and Apoptosis under WWOX Deficiency

The prospect of discovering a cure for cancer has been present for the past two to three decades. Annually, this illness affects approximately 10 million individuals worldwide. Anticancer medications are pivotal in treating cancer and other malignant diseases. In this paper, the physical properties and chemical reactions associated with the anticancer medications of various topological indices (TIs) have been established. Additionally, we have discussed the degree-based TIs and their Quantitative Structure-Property Relationship (QSPR) analysis. In mathematical chemistry, molecular descriptors are essential, particularly for researchers investigating Quantitative Structure-Activity Relationship (QSAR) and QSPR models. The goal of the QSPR study is to establish a mathematical relationship between the properties under investigation (such as boiling point and flash point) and various descriptors related to the molecular structure of the drugs. Furthermore, we show the correlation with the physicochemical properties of anticancer medications.

Clustering as an exploratory technique has been a promising approach for performing data analysis. In this paper, we propose a non-parametric Bayesian inference to address clustering problem. This approach is based on infinite multivariate Beta mixture models constructed through the framework of Dirichlet process. We apply an accelerated variational method to learn the model. The motivation behind proposing this technique is that Dirichlet process mixture models are capable to fit the data where the number of components is unknown. For large-scale data, this approach is computationally expensive. We overcome this problem with the help of accelerated Dirichlet process mixture models. Moreover, the truncation is managed using kd-trees. The performance of the model is validated on real medical applications and compared to three other similar alternatives. The results show the outperformance of our proposed framework.