AI Medical Compendium Journal:
Molecules (Basel, Switzerland)

Showing 71 to 80 of 243 articles

Traditional Machine and Deep Learning for Predicting Toxicity Endpoints.

Molecules (Basel, Switzerland)
Molecular structure property modeling is an increasingly important tool for predicting compounds with desired properties due to the expensive and resource-intensive nature and the problem of toxicity-related attrition in late phases during drug disco...

An Efficient Approach to Large-Scale Ab Initio Conformational Energy Profiles of Small Molecules.

Molecules (Basel, Switzerland)
Accurate conformational energetics of molecules are of great significance to understand maby chemical properties. They are also fundamental for high-quality parameterization of force fields. Traditionally, accurate conformational profiles are obtaine...

Machine Learning Models to Predict Protein-Protein Interaction Inhibitors.

Molecules (Basel, Switzerland)
Protein-protein interaction (PPI) inhibitors have an increasing role in drug discovery. It is hypothesized that machine learning (ML) algorithms can classify or identify PPI inhibitors. This work describes the performance of different algorithms and ...

A Review on Data Fusion of Multidimensional Medical and Biomedical Data.

Molecules (Basel, Switzerland)
Data fusion aims to provide a more accurate description of a sample than any one source of data alone. At the same time, data fusion minimizes the uncertainty of the results by combining data from multiple sources. Both aim to improve the characteriz...

Application of Deep-Learning Algorithm Driven Intelligent Raman Spectroscopy Methodology to Quality Control in the Manufacturing Process of Guanxinning Tablets.

Molecules (Basel, Switzerland)
Coupled with the convolutional neural network (CNN), an intelligent Raman spectroscopy methodology for rapid quantitative analysis of four pharmacodynamic substances and soluble solid in the manufacture process of Guanxinning tablets was established....

Parameter Optimization of Support Vector Machine to Improve the Predictive Performance for Determination of Aflatoxin B in Peanuts by Olfactory Visualization Technique.

Molecules (Basel, Switzerland)
This study proposes a novel method for detection of aflatoxin B (AFB) in peanuts using olfactory visualization technique. First, 12 kinds of chemical dyes were selected to prepare a colorimetric sensor to assemble olfactory visualization system, whic...

Adera2.0: A Drug Repurposing Workflow for Neuroimmunological Investigations Using Neural Networks.

Molecules (Basel, Switzerland)
Drug repurposing in the context of neuroimmunological (NI) investigations is still in its primary stages. Drug repurposing is an important method that bypasses lengthy drug discovery procedures and focuses on discovering new usages for known medicati...

Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks.

Molecules (Basel, Switzerland)
The classification of biological neuron types and networks poses challenges to the full understanding of the human brain's organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morpholog...

Marker-Independent Food Identification Enabled by Combing Machine Learning Algorithms with Comprehensive GC × GC/TOF-MS.

Molecules (Basel, Switzerland)
Reliable methods are always greatly desired for the practice of food inspection. Currently, most food inspection techniques are mainly dependent on the identification of special components, which neglect the combination effects of different component...

Graph Neural Network for Protein-Protein Interaction Prediction: A Comparative Study.

Molecules (Basel, Switzerland)
Proteins are the fundamental biological macromolecules which underline practically all biological activities. Protein-protein interactions (PPIs), as they are known, are how proteins interact with other proteins in their environment to perform biolog...