Paper Title

DRUG REPURPOSING: A STUDY OF DRUG TARGET INDICATION (DTI) RELATIONSHIP WITH MACHINE LEARNING

Abstract

Today We have huge amount of data in the field of biological field, and we have also well-formed multiple machine learning algorithms, by this we can speed up the drug development process. This process may increase, or speed up, drug discovery and drug development process. It gives d help in planning to preclinical phase and also better understanding about drug target indication ane can take help in future. This automation of the drug production process may be the vital to solving the recent concern of low profitability rate in pharmaceutical companies. In this study, our main aim to find new interaction for existing drugs in order to minimize the expense and time of drug development. There are three ways to deal with look at drug repurposing: disease driven method, target driven method, and drug driven method. Disease driven method recognize comfortable associations between an old and another sign. A target driven philosophy interfaces a known objective and towards its set up drug to another sign and last drug driven methodology interfaces a known drug to another target and its related sign.
KEYWORDS : Drug discovery, Drug repurposing, Machine learning algorithm, Drug Target Indication

Paper Title

ANALYSIS OF ANTI-CANCER ACTIVITY AND BIOCHEMICAL ACTIVITY OF COMMON SPICES

Abstract

The anti-cancer activity and biochemical effects of aqueous and ethanolic extracts of twelve common kitchen spices were analyzed using the K562 chronic myeloid leukemia cell line. The spices tested included black pepper, clove, cardamom, cinnamon, fenugreek, star anise, moringa, nutmeg, coriander, mustard, cumin, and carom. The results indicated that ethanolic extracts demonstrated significant anti-leukemic activity compared to that of aqueous extracts. Proteomic analysis revealed significant alterations in protein levels following treatment, highlighting the biochemical impact of these spice extracts.
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