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Pharmaceutics Informatics: Bio/Chemoinformatics in Drug Delivery
Whilst bioinformatics deals with the biological receptors and proteins (biological macromolecules) and their manipulation, the chemoinformatics is...
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Exploring the Role of Chemoinformatics in Accelerating Drug Discovery: A Computational Approach
Cheminformatics and its role in drug discovery is expected to be the privileged approach in handling large number of chemical datasets. This approach...
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Chemoinformatics Study of Benzodiazepine-1, 2, 3-triazole Derivatives Targeting Butyrylcholinesterase
This study aims to assess the potential bioactivity of newly designed benzodiazepine-1,2,3-triazole derivatives using in-silico methodologies, with a...
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Computational Tools for Cancer Nanomedicine
Computational tools in cancer nanomedicine consist of many approaches that enable progress at the convergence of computer engineering and medical...
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Graph Kernel Learning for Predictive Toxicity Models
Graph-driven techniques have been widely used in chemoinformatics and bioinformatics. It is of a great beneficial to develop toxicity prediction...
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Progress on Open Chemoinformatic Tools for Drug Discovery
Informatics plays a fundamental role in many chemistry applications giving rise to the consolidation of well-established disciplines such as...
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Artificial Intelligence in Drug Discovery and Development
Recently, machine learning (ML) and artificial intelligence (AI) have gained popularity in the healthcare sector. In the field of drug discovery and...
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Health Risk Assessment of Environmental Chemicals Pre-Emptive and Integrated Approaches
This book presents the frontier research of toxicology and health risk assessment of chemicals. First, it provides an overview of the current methods...
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Applications of Computational Methods in Natural Products Based Drug Discovery
Since antiquity, natural resources, mainly plants, have been used for medicinal purposes. The primitive usage was based on a trial-and-error...
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Developing an AI-based prediction model for anaphylactic shock from injection drugs using Japanese real-world data and chemical structure-based analysis
BackgroundThis study aims to develop an AI-based prediction model for injection drugs that cause anaphylactic shock using Japanese Real-World Data...
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Conceptual DFT as a chemoinformatics tool for the study of the Taltobulin anticancer peptide
ObjectiveA well-behaved model chemistry previously validated for the study of the chemical reactivity of peptides was considered for the calculation...
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AI: Catalyst for Drug Discovery and Development
This abstract explores the multifaceted roles of AI in expediting the drug development process. AI-driven algorithms analyze vast datasets,...
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QSAR Methods
This chapter introduces the basis of computational chemistry and discusses how computational methods have been extended from physical to biological...
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Recent Advances in Computational Modeling of BACE1 Inhibitors as Anti-Alzheimer Agents
A growing number of people worldwide are being affected by aging-associated neurodegenerative illnesses, the most prevalent of which, Alzheimer’s, is...
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Dietary Components as Promoters of Medicinal Activity in Alzheimer’s Disease
Alzheimer’s disease (AD) is among the most serious neurodegenerative diseases with poor diagnosis and treatment. AD is one of the most common types...
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Cumulative effects of exercise training and consumption of propolis on managing diabetic dyslipidemia in adult women: a single-blind, randomized, controlled trial with pre–post-intervention assessments
Dyslipidemia is an imbalance of various lipids, and propolis, as a natural resinous viscos mixture made by Apis mellifera L. could improve in this...
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In Silico Search for Chiral Drug Compounds
All optical isomers of an optically active medicinal substance require experimental and clinical testing. In this process, as a rule, in silico...
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Machine Learning and Life Sciences
Machine learning has tremendous applications in diverse domains of Life Sciences, including Health Sciences, basic biology research, clinical...
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Dietary Components as Promoters of Medicinal Activity in Alzheimer’s Disease
Alzheimer’s disease (AD) is among the most serious neurodegenerative diseases with poor diagnosis and treatment. AD is one of the most common types...
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AI and Big Data for Drug Discovery
The design of new drugs is expensive, laborious, and complicated, and the vast majority of new drugs fail in clinical trials. Artificial...
