Artificial intelligence in cosmetic dermatology: a systematic literature review
P Vatiwutipong, S Vachmanus, T Noraset… - IEEE Access, 2023 - ieeexplore.ieee.org
Over the last ten years, the field of dermatology has experienced significant advancements
through the utilization of artificial intelligence (AI) technologies. The adoption of such …
through the utilization of artificial intelligence (AI) technologies. The adoption of such …
ToxinPred2: an improved method for predicting toxicity of proteins
Proteins/peptides have shown to be promising therapeutic agents for a variety of diseases.
However, toxicity is one of the obstacles in protein/peptide-based therapy. The current study …
However, toxicity is one of the obstacles in protein/peptide-based therapy. The current study …
Applications of artificial intelligence and machine learning on critical materials used in cosmetics and personal care formulation design
The applications of Artificial intelligence (AI) and machine learning (ML) approaches are
rising in formula optimization, ingredients selection, performance prediction, and structure …
rising in formula optimization, ingredients selection, performance prediction, and structure …
Sequence-based prediction of plant allergenic proteins: machine learning classification approach
This Article proposes a novel chemometric approach to understanding and exploring the
allergenic nature of food proteins. Using machine learning methods (supervised and …
allergenic nature of food proteins. Using machine learning methods (supervised and …
IL13Pred: A method for predicting immunoregulatory cytokine IL-13 inducing peptides
Abstract Background Interleukin 13 (IL-13) is an immunoregulatory cytokine, primarily
released by activated T-helper 2 cells. IL-13 induces the pathogenesis of many allergic …
released by activated T-helper 2 cells. IL-13 induces the pathogenesis of many allergic …
Qualitative and quantitative prediction of food allergen epitopes based on machine learning combined with in vitro experimental validation
XX Yu, MQ Liu, XY Li, YH Zhang, BJ Tao - Food chemistry, 2023 - Elsevier
An allergen epitope is a part of molecules that can specifically bind to immunoglobulin E
(IgE), causing an allergic reactions. To predict protein epitopes and their binding ability to …
(IgE), causing an allergic reactions. To predict protein epitopes and their binding ability to …
pLM4Alg: Protein Language Model-Based Predictors for Allergenic Proteins and Peptides
The rising prevalence of allergy demands efficient and accurate bioinformatic tools to
expedite allergen identification and risk assessment while also reducing wet experiment …
expedite allergen identification and risk assessment while also reducing wet experiment …
Computer-aided prediction of inhibitors against STAT3 for managing COVID-19 associated cytokine storm
Background Proinflammatory cytokines are correlated with the severity of disease in patients
with COVID-19. IL6-mediated activation of STAT3 proliferates proinflammatory responses …
with COVID-19. IL6-mediated activation of STAT3 proliferates proinflammatory responses …
A web server for predicting and scanning of IL-5 inducing peptides using alignment-free and alignment-based method
LD Naorem, N Sharma, GPS Raghava - Computers in biology and …, 2023 - Elsevier
Abstract Interleukin-5 (IL-5) can act as an enticing therapeutic target due to its pivotal role in
several eosinophil-mediated diseases. The aim of this study is to develop a model for …
several eosinophil-mediated diseases. The aim of this study is to develop a model for …
An intelligent diabetes classification and perception framework based on ensemble and deep learning method
Sugar in the blood can harm individuals and their vital organs, potentially leading to
blindness, renal illness, as well as kidney and heart diseases. Globally, diabetic patients …
blindness, renal illness, as well as kidney and heart diseases. Globally, diabetic patients …