Research in Bioinformatics

QSAR and ML: A Powerful Combination for Drug Discovery

Machine Learning

Quantitative structure-activity relationship (QSAR) is a method that uses mathematical models to predict the biological activity or physicochemical property of a molecule based on its structure. QSAR has been widely used in drug discovery, environmental toxicology, and chemical risk assessment for decades. However, traditional QSAR models often suffer from limitations such as low accuracy, poor […]

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Bioinformatics in Pharmacogenomics: A Powerful Combination for Personalized Medicine

Research in Bioinformatics

Pharmacogenomics is the study of how genetic variations affect drug response and toxicity in individuals and populations. It aims to optimize drug therapy by tailoring the right drug, dose, and regimen for each patient based on their genetic profile. Pharmacogenomics has the potential to improve patient outcomes, reduce adverse drug reactions, and lower healthcare costs.

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Drug Designing for beginners

Drug Designing for beginners

CADD

Drug designing is the process of finding new medications based on the knowledge of a biological target, such as a protein or a nucleic acid. Drug designing can be done by using various computational tools that can help predict the interaction and binding of a potential drug molecule with the target. In this blog,  There

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Drug Target interaction analysis using  Machine Learning

Machine Learning

In the ever-evolving landscape of healthcare, the fusion of machine learning and drug discovery has emerged as a transformative force. One of the key frontiers in this collaboration is the analysis of drug-target interactions, a realm where machine learning is reshaping the way we identify and understand potential therapeutic opportunities. Deciphering Drug-Target Interactions: A Vital

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Next-Generation Sequencing: Challenges and Future Direction

NGS

Next-generation sequencing (NGS) is a powerful technology that has revolutionized genomics research by enabling the rapid and comprehensive analysis of DNA and RNA molecules. NGS can sequence millions of DNA fragments simultaneously, providing insights into genome structure, genetic variations, gene expression, and epigenetic modifications. NGS has a wide range of applications in various fields, such

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Advancements in Next-Generation Sequencing: A Game-Changer in Bioinformatics

Advancements in Next-Generation Sequencing: A Game-Changer in Bioinformatics

NGS

Next-Generation Sequencing (NGS) has revolutionised the field of bioinformatics by enabling the rapid and cost-effective analysis of genomic data. Let’s explore the transformative impact of NGS on bioinformatics, its key advantages over traditional sequencing methods, and how it has opened new avenues for groundbreaking discoveries in genomics research. Next-Generation Sequencing Vs traditional methods: NGS has

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