AIMC Topic: Protein Binding

Clear Filters Showing 941 to 950 of 954 articles

Detecting reliable non interacting proteins (NIPs) significantly enhancing the computational prediction of protein-protein interactions using machine learning methods.

Molecular bioSystems Mar 1, 2016
Protein-protein interactions (PPIs) play a vital role in most biological processes. Hence their comprehension can promote a better understanding of the mechanisms underlying living systems. However, besides the cost and the time limitation involved i...
Machine Learning Databases, Protein Sample Size Probability Protein Interaction Mapping Reproducibility of Results ROC Curve Protein Binding Computational Biology
View on PubMed DOI

Identification of Glucose-Binding Pockets in Human Serum Albumin Using Support Vector Machine and Molecular Dynamics Simulations.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2016
Human Serum Albumin (HSA) has been suggested to be an alternate biomarker to the existing Hemoglobin-A1c (HbA1c) marker for glycemic monitoring. Development and usage of HSA as an alternate biomarker requires the identification of glycation sites, or...
Computational Biology Support Vector Machine Glucose Molecular Dynamics Simulation Humans Serum Albumin Protein Binding Binding Sites
View on PubMed DOI

A novel machine learning method for cytokine-receptor interaction prediction.

Combinatorial chemistry & high throughput screening Jan 1, 2016
Most essential functions are associated with various protein-protein interactions, particularly the cytokine-receptor interaction. Knowledge of the heterogeneous network of cytokine- receptor interactions provides insights into various human physiolo...
Databases, Protein High-Throughput Screening Assays Receptors, Cytokine Machine Learning Cytokines Protein Binding Humans
View on PubMed DOI

A systematic approach to prioritize drug targets using machine learning, a molecular descriptor-based classification model, and high-throughput screening of plant derived molecules: a case study in oral cancer.

Molecular bioSystems Dec 1, 2015
Systems-biology inspired identification of drug targets and machine learning-based screening of small molecules which modulate their activity have the potential to revolutionize modern drug discovery by complementing conventional methods. To utilize ...
Humans Machine Learning Drug Discovery Cell Line, Tumor Gene Expression Regulation, Neoplastic Antineoplastic Agents, Phytogenic Receptors, CXCR4 Models, Molecular ROC Curve Gene Regulatory Networks Protein Binding Computational Biology Binding Sites Protein Interaction Mapping Mouth Neoplasms High-Throughput Screening Assays Molecular Conformation
View on PubMed DOI

Distinct Transcriptional and Anti-Mycobacterial Profiles of Peripheral Blood Monocytes Dependent on the Ratio of Monocytes: Lymphocytes.

EBioMedicine Nov 1, 2015
The ratio of monocytes and lymphocytes (ML ratio) in peripheral blood is associated with tuberculosis and malaria disease risk and cancer and cardiovascular disease outcomes. We studied anti-mycobacterial function and the transcriptome of monocytes i...
Disease Resistance Mycobacterium Binding Sites Leukocyte Count Interferons Protein Binding Adult Monocytes Transcription Factors Humans Male Signal Transduction Tuberculosis Female Gene Expression Profiling Lymphocytes Young Adult Transcriptome Disease Susceptibility
View on PubMed DOI

Predicting selective liver X receptor β agonists using multiple machine learning methods.

Molecular bioSystems May 1, 2015
Liver X receptor (LXR) α and β are cholesterol sensors; they respond to excess cholesterol and stimulate reverse cholesterol transport. Activating LXRs represents a promising therapeutic option for dyslipidemia. However, activating LXRα may cause unw...
Models, Theoretical Liver X Receptors Orphan Nuclear Receptors Humans Machine Learning Algorithms Reproducibility of Results Drug Discovery Protein Binding
View on PubMed DOI

[Immunochromatographic Test System for the Detection of T-2 Toxin].

Prikladnaia biokhimiia i mikrobiologiia Jan 1, 2015
An immunochromatographic test system was developed for the detection of T-2 toxin (T2T), which is one of priority contaminants of cereals. The detection is based on the competition between T2T in the sample and the T2T-protein conjugate immobilized o...
Fusarium Immunoconjugates Binding, Competitive Animals T-2 Toxin Chromatography, Affinity Zea mays Methanol Edible Grain Antibodies, Monoclonal Reagent Strips Gold Protein Binding Mice Metal Nanoparticles Food Contamination Limit of Detection
View on PubMed

The quantitative prediction of HLA-B*2705 peptide binding affinities using Support Vector Regression to gain insights into its role for the Spondyloarthropathies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jan 1, 2015
Computational methods are increasingly utilised in many immunoinformatics problems such as the prediction of binding affinity of peptides. The peptides could provide valuable insight into the drug design and development such as vaccines. Moreover, th...
Humans Peptides Protein Binding Computational Biology Support Vector Machine Spondylarthropathies Alleles HLA-B27 Antigen
View on PubMed DOI

Predicting Protein-Protein Interaction Sites with a Novel Membership Based Fuzzy SVM Classifier.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
Predicting residues that participate in protein-protein interactions (PPI) helps to identify, which amino acids are located at the interface. In this paper, we show that the performance of the classical support vector machine (SVM) algorithm can furt...
Molecular Sequence Data Sequence Alignment Sequence Analysis, Protein Fuzzy Logic Models, Statistical Models, Chemical Amino Acid Sequence Pattern Recognition, Automated Binding Sites Protein Interaction Mapping Humans Algorithms Computer Simulation Protein Binding
View on PubMed DOI

Analysis of Drug Design for a Selection of G Protein-Coupled Neuro- Receptors Using Neural Network Techniques.

Current computer-aided drug design Jan 1, 2015
A study is presented on how well possible drug-molecules can be predicted with respect to their function and binding to a selection of neuro-receptors by the use of artificial neural networks. The ligands investigated in this study are chosen to be c...
Receptor, Serotonin, 5-HT2B Drug Design Receptors, Opioid, mu Protein Binding Ligands Receptor, Metabotropic Glutamate 5 Humans Neural Networks, Computer
View on PubMed DOI
Popular Topics
Recent Journals