AIMC Topic: Hemolysis
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A Hemolysis Image Detection Method Based on GAN-CNN-ELM.
Computational and mathematical methods in medicine
Feb 22, 2022
Since manual hemolysis test methods are given priority with practical experience and its cost is high, the characteristics of hemolysis images are studied. A hemolysis image detection method based on generative adversarial networks (GANs) and convolu...
HemoNet: Predicting hemolytic activity of peptides with integrated feature learning.
Journal of bioinformatics and computational biology
Aug 5, 2021
Quantifying the hemolytic activity of peptides is a crucial step in the discovery of novel therapeutic peptides. Computational methods are attractive in this domain due to their ability to guide wet-lab experimental discovery or screening of peptides...
Prediction of Anticancer Peptides with High Efficacy and Low Toxicity by Hybrid Model Based on 3D Structure of Peptides.
International journal of molecular sciences
May 26, 2021
Recently, anticancer peptides (ACPs) have emerged as unique and promising therapeutic agents for cancer treatment compared with antibody and small molecule drugs. In addition to experimental methods of ACPs discovery, it is also necessary to develop ...
Machine learning-guided discovery and design of non-hemolytic peptides.
Scientific reports
Oct 6, 2020
Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biol...
HAPPENN is a novel tool for hemolytic activity prediction for therapeutic peptides which employs neural networks.
Scientific reports
Jul 2, 2020
The growing prevalence of resistance to antibiotics motivates the search for new antibacterial agents. Antimicrobial peptides are a diverse class of well-studied membrane-active peptides which function as part of the innate host defence system, and f...
In Silico Prediction of Hemolytic Toxicity on the Human Erythrocytes for Small Molecules by Machine-Learning and Genetic Algorithm.
Journal of medicinal chemistry
Jul 8, 2019
Hemolytic toxicity of small molecules, as one of the important ADMET end points, can cause the lysis of erythrocytes membrane and leaking of hemoglobin into the blood plasma, which leads to various side effects. Thus, it is very crucial to assess the...
Machine learning algorithms for the detection of spurious white blood cell differentials due to erythrocyte lysis resistance.
Journal of clinical pathology
Apr 16, 2019
AIMS: Red blood cell (RBC) lysis resistance interferes with white blood cell (WBC) count and differential; still, its detection relies on the identification of an abnormal scattergram, and this is not clearly adverted by specific flags in the Beckman...
Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods.
Chemical research in toxicology
Apr 9, 2019
Saponins are a type of compounds bearing a hydrophobic steroid/triterpenoid moiety and hydrophilic carbohydrate branches. The majority of the saponins demonstrate a broad range of prominent pharmacological activities. Nevertheless, many saponins also...
Multi-Objective Genetic Algorithm Assisted by an Artificial Neural Network Metamodel for Shape Optimization of a Centrifugal Blood Pump.
Artificial organs
Nov 18, 2018
A centrifugal blood pump is a common type of the pump used as a left ventricular assist device (LVAD) in the medical industries. The reduction of the LVADs hemolysis level to reduce the blood damage is one of the major concerns in designing of such d...
Exploring the phenolic profile, antioxidant, antidiabetic and anti-hemolytic potential of Prunus avium vegetal parts.
Food research international (Ottawa, Ont.)
Sep 2, 2018
The aim of the present work was to evaluate the phenolic profile of leaves, stems and flowers of P. avium and their biological potential. For this purpose, two extracts of each matrix (hydroethanolic and infusion) were prepared. A total of twenty-six...
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