AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Amino Acids

Showing 91 to 100 of 222 articles

Clear Filters

Computational identification of ubiquitination sites in Arabidopsis thaliana using convolutional neural networks.

Plant molecular biology
We developed two CNNs for predicting ubiquitination sites in Arabidopsis thaliana, demonstrated their competitive performance, analyzed amino acid physicochemical properties and the CNN structures, and predicted ubiquitination sites in Arabidopsis. A...

QSSR Modeling of Bacillus Subtilis Lipase A Peptide Collision Cross-Sections in Ion Mobility Spectrometry: Local Descriptor Versus Global Descriptor.

The protein journal
To investigate the structure-dependent peptide mobility behavior in ion mobility spectrometry (IMS), quantitative structure-spectrum relationship (QSSR) is systematically modeled and predicted for the collision cross section Ω values of totally 162 s...

A Novel Protein Mapping Method for Predicting the Protein Interactions in COVID-19 Disease by Deep Learning.

Interdisciplinary sciences, computational life sciences
The new type of corona virus (SARS-COV-2) emerging in Wuhan, China has spread rapidly to the world and has become a pandemic. In addition to having a significant impact on daily life, it also shows its effect in different areas, including public heal...

Incorporating a transfer learning technique with amino acid embeddings to efficiently predict N-linked glycosylation sites in ion channels.

Computers in biology and medicine
Glycosylation is a dynamic enzymatic process that attaches glycan to proteins or other organic molecules such as lipoproteins. Research has shown that such a process in ion channel proteins plays a fundamental role in modulating ion channel functions...

Free amino acids in African indigenous vegetables: Analysis with improved hydrophilic interaction ultra-high performance liquid chromatography tandem mass spectrometry and interactive machine learning.

Journal of chromatography. A
A hydrophilic interaction (HILIC) ultra-high performance liquid chromatography (UHPLC) with triple quadrupole tandem mass spectrometry (MS/MS) method was developed and validated for the quantification of 21 free amino acids (AAs). Compared to publish...

PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.

Computational and mathematical methods in medicine
Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its...

Application of artificial neural networks to predict multiple quality of dry-cured ham based on protein degradation.

Food chemistry
This study investigated protein degradation and quality changes during the processing of dry-cured ham, and then established the multiple quality prediction model based on protein degradation. From the raw material to the curing period, proteolysis i...

SPOTONE: Hot Spots on Protein Complexes with Extremely Randomized Trees via Sequence-Only Features.

International journal of molecular sciences
Protein Hot-Spots (HS) are experimentally determined amino acids, key to small ligand binding and tend to be structural landmarks on protein-protein interactions. As such, they were extensively approached by structure-based Machine Learning (ML) pred...

IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides.

Journal of chemical information and modeling
Antimicrobial peptides (AMPs) are at the focus of attention due to their therapeutic importance and developing computational tools for the identification of efficient antibiotics from the primary structure. Here, we utilized the CNMR spectral of amin...

Combining mechanistic and machine learning models for predictive engineering and optimization of tryptophan metabolism.

Nature communications
Through advanced mechanistic modeling and the generation of large high-quality datasets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can be c...