AIMC Topic: Drug Discovery

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Network-based screen in iPSC-derived cells reveals therapeutic candidate for heart valve disease.

Science (New York, N.Y.) Dec 10, 2020
Mapping the gene-regulatory networks dysregulated in human disease would allow the design of network-correcting therapies that treat the core disease mechanism. However, small molecules are traditionally screened for their effects on one to several o...
Calcinosis Aortic Valve Stenosis Aortic Valve Disease Models, Animal Mice, Inbred C57BL Gene Expression Regulation Nitriles Small Molecule Libraries Drug Evaluation, Preclinical Thiazoles Animals Drug Discovery Gene Regulatory Networks Mice RNA-Seq Machine Learning Algorithms Humans Haploinsufficiency Aortic Valve Disease Induced Pluripotent Stem Cells Receptor, Notch1
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Scaffold-Constrained Molecular Generation.

Journal of chemical information and modeling Dec 10, 2020
One of the major applications of generative models for drug discovery targets the lead-optimization phase. During the optimization of a lead series, it is common to have scaffold constraints imposed on the structure of the molecules designed. Without...
Algorithms Drug Design Neural Networks, Computer Probability Drug Discovery
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Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.

Medicinal research reviews Dec 9, 2020
Neurological disorders significantly outnumber diseases in other therapeutic areas. However, developing drugs for central nervous system (CNS) disorders remains the most challenging area in drug discovery, accompanied with the long timelines and high...
Algorithms Humans Drug Discovery Central Nervous System Diseases Artificial Intelligence Machine Learning
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Editorial for the Special Section "Artificial Intelligence in Drug Discovery".

Drug discovery today. Technologies Dec 7, 2020
Drug Discovery Humans Data Mining Artificial Intelligence
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Advanced machine-learning techniques in drug discovery.

Drug discovery today Dec 5, 2020
The popularity of machine learning (ML) across drug discovery continues to grow, yielding impressive results. As their use increases, so do their limitations become apparent. Such limitations include their need for big data, sparsity in data, and the...
Animals Drug Discovery Big Data Humans Machine Learning
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Innovative approaches in CNS drug discovery.

Therapie Dec 5, 2020
Central nervous system disorders remain the leading causes of mortality and morbidity worldwide, affecting more than 1 billion patients. This therapeutic area suffers from high unmet medical needs and the search for innovative approaches to identify ...
Central Nervous System Agents Humans Artificial Intelligence Drug Discovery Big Data Animals
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Analysis of Biological Screening Compounds with Single- or Multi-Target Activity via Diagnostic Machine Learning.

Biomolecules Nov 27, 2020
Predicting compounds with single- and multi-target activity and exploring origins of compound specificity and promiscuity is of high interest for chemical biology and drug discovery. We present a large-scale analysis of compound promiscuity including...
Machine Learning Pharmaceutical Preparations Drug Evaluation, Preclinical Drug Discovery
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Moving targets in drug discovery.

Scientific reports Nov 19, 2020
Drug Discovery is a lengthy and costly process and has faced a period of declining productivity within the last two decades resulting in increasing importance of integrative data-driven approaches. In this paper, data mining and integration is levera...
Drug Discovery Humans Gene Ontology Software Databases, Factual
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DeepSIBA: chemical structure-based inference of biological alterations using deep learning.

Molecular omics Nov 14, 2020
Predicting whether a chemical structure leads to a desired or adverse biological effect can have a significant impact for in silico drug discovery. In this study, we developed a deep learning model where compound structures are represented as graphs ...
Humans Neural Networks, Computer Antineoplastic Agents Software Deep Learning Drug Discovery Structure-Activity Relationship
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Machine Learning Methods in Drug Discovery.

Molecules (Basel, Switzerland) Nov 12, 2020
The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been use...
Bayes Theorem Internet Algorithms Humans Monte Carlo Method Databases, Factual Computational Biology Reproducibility of Results Machine Learning Drug Discovery Support Vector Machine Deep Learning Software
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