AIMC Journal:
International journal of molecular sciences

Showing 261 to 270 of 423 articles

Augmentation of Transcriptomic Data for Improved Classification of Patients with Respiratory Diseases of Viral Origin.

International journal of molecular sciences Feb 24, 2022
To better understand the molecular basis of respiratory diseases of viral origin, high-throughput gene-expression data are frequently taken by means of DNA microarray or RNA-seq technology. Such data can also be useful to classify infected individual...
Humans Neural Networks, Computer Gene Expression Profiling Transcriptome RNA-Seq Gene Ontology Machine Learning COVID-19 Algorithms Reproducibility of Results SARS-CoV-2
View on PubMed DOI

A Transfer-Learning-Based Deep Convolutional Neural Network for Predicting Leukemia-Related Phosphorylation Sites from Protein Primary Sequences.

International journal of molecular sciences Feb 3, 2022
As one of the most important post-translational modifications (PTMs), phosphorylation refers to the binding of a phosphate group with amino acid residues like Ser (S), Thr (T) and Tyr (Y) thus resulting in diverse functions at the molecular level. Ab...
Cluster Analysis Neoplasm Proteins Phosphorylation Peptides Deep Learning ROC Curve Entropy Leukemia Learning Curve Humans Phosphoproteins Neural Networks, Computer Amino Acid Sequence Databases as Topic
View on PubMed DOI

DSResSol: A Sequence-Based Solubility Predictor Created with Dilated Squeeze Excitation Residual Networks.

International journal of molecular sciences Dec 17, 2021
Protein solubility is an important thermodynamic parameter that is critical for the characterization of a protein's function, and a key determinant for the production yield of a protein in both the research setting and within industrial (e.g., pharma...
Amino Acid Sequence Solubility Computational Biology Proteins Models, Chemical Deep Learning
View on PubMed DOI

Molecular Biology in Treatment Decision Processes-Neuro-Oncology Edition.

International journal of molecular sciences Dec 10, 2021
Computational approaches including machine learning, deep learning, and artificial intelligence are growing in importance in all medical specialties as large data repositories are increasingly being optimised. Radiation oncology as a discipline is at...
Humans Machine Learning Biomarkers, Tumor Computational Biology Glioma Radiation Oncology Central Nervous System Neoplasms
View on PubMed DOI

UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning.

International journal of molecular sciences Dec 4, 2021
Umami ingredients have been identified as important factors in food seasoning and production. Traditional experimental methods for characterizing peptides exhibiting umami sensory properties (umami peptides) are time-consuming, laborious, and costly....
Computational Biology Machine Learning Internet Support Vector Machine Taste Algorithms Databases, Protein Dietary Proteins Peptides
View on PubMed DOI

IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds.

International journal of molecular sciences Dec 2, 2021
The parasite species of genus causes Malaria, which remains a major global health problem due to parasite resistance to available Antimalarial drugs and increasing treatment costs. Consequently, computational prediction of new Antimalarial compounds...
Databases, Pharmaceutical Plasmodium falciparum Genome, Protozoan Drug Evaluation, Preclinical Antimalarials Markov Chains Protozoan Proteins Reproducibility of Results Drug Discovery Models, Theoretical Machine Learning Algorithms
View on PubMed DOI

Genome-Wide Mutation Scoring for Machine-Learning-Based Antimicrobial Resistance Prediction.

International journal of molecular sciences Dec 2, 2021
The prediction of antimicrobial resistance (AMR) based on genomic information can improve patient outcomes. Genetic mechanisms have been shown to explain AMR with accuracies in line with standard microbiology laboratory testing. To translate genetic ...
Anti-Infective Agents Genomics Escherichia coli Machine Learning Drug Resistance, Bacterial Genome, Bacterial Mutation Whole Genome Sequencing Pseudomonas aeruginosa
View on PubMed DOI

Unsupervised Representation Learning for Proteochemometric Modeling.

International journal of molecular sciences Nov 28, 2021
In silico protein-ligand binding prediction is an ongoing area of research in computational chemistry and machine learning based drug discovery, as an accurate predictive model could greatly reduce the time and resources necessary for the detection a...
Proteins Ligands Unsupervised Machine Learning Quantitative Structure-Activity Relationship Cheminformatics
View on PubMed DOI

Evaluation of Deep Neural Network ProSPr for Accurate Protein Distance Predictions on CASP14 Targets.

International journal of molecular sciences Nov 27, 2021
The field of protein structure prediction has recently been revolutionized through the introduction of deep learning. The current state-of-the-art tool AlphaFold2 can predict highly accurate structures; however, it has a prohibitively long inference ...
Protein Structural Elements Protein Folding Sequence Alignment Humans Software Design Proteins Neural Networks, Computer Amino Acid Sequence Computational Biology Protein Conformation
View on PubMed DOI

Sparsely Connected Autoencoders: A Multi-Purpose Tool for Single Cell omics Analysis.

International journal of molecular sciences Nov 25, 2021
BACKGROUND: Biological processes are based on complex networks of cells and molecules. Single cell multi-omics is a new tool aiming to provide new incites in the complex network of events controlling the functionality of the cell.
Adenocarcinoma of Lung Humans Neural Networks, Computer Machine Learning Computational Biology Cluster Analysis Single-Cell Analysis Exome Sequencing Lung Neoplasms
View on PubMed DOI
Popular Topics
Popular Journals