AIMC Topic: Cheminformatics

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Discrimination of white wine ageing based on untarget peak picking approach with multi-class target coupled with machine learning algorithms.

Food chemistry Feb 16, 2021
The complexity of the chemical reactions occurring during white wine storage, such as oxidation turns the capacity of prediction and consequently the capacity to avoid it extremely difficult. This study proposes an untarget methodology based on machi...
Esters Cheminformatics Time Factors Oxidation-Reduction Wine Machine Learning
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Classification models and SAR analysis on CysLT1 receptor antagonists using machine learning algorithms.

Molecular diversity Feb 3, 2021
Cysteinyl leukotrienes 1 (CysLT1) receptor is a promising drug target for rhinitis or other allergic diseases. In our study, we built classification models to predict bioactivities of CysLT1 receptor antagonists. We built a dataset with 503 CysLT1 re...
Protein Binding Models, Molecular Molecular Structure Drug Discovery Cheminformatics Algorithms ROC Curve Machine Learning Reproducibility of Results Leukotriene Antagonists Quantitative Structure-Activity Relationship Receptors, Leukotriene Binding Sites
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Improved Deep Learning Based Method for Molecular Similarity Searching Using Stack of Deep Belief Networks.

Molecules (Basel, Switzerland) Dec 29, 2020
Virtual screening (VS) is a computational practice applied in drug discovery research. VS is popularly applied in a computer-based search for new lead molecules based on molecular similarity searching. In chemical databases similarity searching is us...
Bayes Theorem Pharmaceutical Preparations Cheminformatics Deep Learning Principal Component Analysis Databases, Pharmaceutical Drug Design Drug Discovery Neural Networks, Computer
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Electron-Passing Neural Networks for Atomic Charge Prediction in Systems with Arbitrary Molecular Charge.

Journal of chemical information and modeling Dec 16, 2020
Atomic charges are critical quantities in molecular mechanics and molecular dynamics, but obtaining these quantities requires heuristic choices based on atom typing or relatively expensive quantum mechanical computations to generate a density to be p...
Machine Learning Molecular Dynamics Simulation Electrons Neural Networks, Computer Cheminformatics
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Virtual screening of anti-HIV1 compounds against SARS-CoV-2: machine learning modeling, chemoinformatics and molecular dynamics simulation based analysis.

Scientific reports Nov 23, 2020
COVID-19 caused by the SARS-CoV-2 is a current global challenge and urgent discovery of potential drugs to combat this pandemic is a need of the hour. 3-chymotrypsin-like cysteine protease (3CLpro) enzyme is the vital molecular target against the SAR...
Anti-HIV Agents Antiviral Agents Molecular Dynamics Simulation Drug Evaluation, Preclinical Drug Repositioning SARS-CoV-2 Molecular Docking Simulation Deep Learning Humans COVID-19 Infectious bronchitis virus Protease Inhibitors Cheminformatics HIV-1 Coronavirus 3C Proteases COVID-19 Drug Treatment
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Machine-Learning and Chemicogenomics Approach Defines and Predicts Cross-Talk of Hippo and MAPK Pathways.

Cancer discovery Nov 18, 2020
Hippo pathway dysregulation occurs in multiple cancers through genetic and nongenetic alterations, resulting in translocation of YAP to the nucleus and activation of the TEAD family of transcription factors. Unlike other oncogenic pathways such as RA...
Cheminformatics Hippo Signaling Pathway Signal Transduction MAP Kinase Signaling System Humans Genomics Computational Biology Machine Learning
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Self-Optimizing Support Vector Elastic Net.

Analytical chemistry Nov 9, 2020
Chemometrics is widely used to solve various quantitative and qualitative problems in analytical chemistry. A self-optimizing chemometrics method facilitates scientists to exploit the advantages of chemometrics. In this report, a parameter-free suppo...
Linear Models Cheminformatics Support Vector Machine
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A Recurrent Neural Network model to predict blood-brain barrier permeability.

Computational biology and chemistry Sep 24, 2020
The rapid development of computational methods and the increasing volume of chemical and biological data have contributed to an immense growth in chemical research. This field of study is known as "chemoinformatics," which is a discipline that uses m...
Algorithms Cheminformatics Models, Biological Databases, Chemical Blood-Brain Barrier Pharmaceutical Preparations Quantitative Structure-Activity Relationship Deep Learning Permeability
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Hybrid Harris hawks optimization with cuckoo search for drug design and discovery in chemoinformatics.

Scientific reports Sep 2, 2020
One of the major drawbacks of cheminformatics is a large amount of information present in the datasets. In the majority of cases, this information contains redundant instances that affect the analysis of similarity measurements with respect to drug d...
Humans Machine Learning Support Vector Machine Algorithms Heuristics Drug Design Cheminformatics
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Impact of Chemist-In-The-Loop Molecular Representations on Machine Learning Outcomes.

Journal of chemical information and modeling Aug 18, 2020
The development of molecular descriptors is a central challenge in cheminformatics. Most approaches use algorithms that extract atomic environments or end-to-end machine learning. However, a looming question is that how do these approaches compare wi...
Cheminformatics Machine Learning Algorithms
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