AIMC Topic: Membrane Proteins
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Models of logistic regression analysis, support vector machine, and back-propagation neural network based on serum tumor markers in colorectal cancer diagnosis.
Genetics and molecular research : GMR
May 13, 2016
We evaluated the application of three machine learning algorithms, including logistic regression, support vector machine and back-propagation neural network, for diagnosing congenital heart disease and colorectal cancer. By inspecting related serum t...
Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli.
Nucleus (Austin, Tex.)
Mar 10, 2016
A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm ...
A Prediction Model for Membrane Proteins Using Moments Based Features.
BioMed research international
Feb 15, 2016
The most expedient unit of the human body is its cell. Encapsulated within the cell are many infinitesimal entities and molecules which are protected by a cell membrane. The proteins that are associated with this lipid based bilayer cell membrane are...
Enhancing the Prediction of Transmembrane β-Barrel Segments with Chain Learning and Feature Sparse Representation.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 11, 2016
Transmembrane β-barrels (TMBs) are one important class of membrane proteins that play crucial functions in the cell. Membrane proteins are difficult wet-lab targets of structural biology, which call for accurate computational prediction approaches. H...
Prediction Enhancement of Residue Real-Value Relative Accessible Surface Area in Transmembrane Helical Proteins by Solving the Output Preference Problem of Machine Learning-Based Predictors.
Journal of chemical information and modeling
Oct 20, 2015
The α-helical transmembrane proteins constitute 25% of the entire human proteome space and are difficult targets in high-resolution wet-lab structural studies, calling for accurate computational predictors. We present a novel sequence-based method ca...
Mem-mEN: Predicting Multi-Functional Types of Membrane Proteins by Interpretable Elastic Nets.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 28, 2015
Membrane proteins play important roles in various biological processes within organisms. Predicting the functional types of membrane proteins is indispensable to the characterization of membrane proteins. Recent studies have extended to predicting si...
Cheminformatics Based Machine Learning Models for AMA1-RON2 Abrogators for Inhibiting Plasmodium falciparum Erythrocyte Invasion.
Molecular informatics
Jul 17, 2015
Malaria remains a dreadful disease by putting every year about 3.4 billion people at risk and resulting into mortality of 627 thousand people worldwide. Existing therapies based upon Quinines and Artemisinin-based combination therapies have started s...
Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma.
Tumori
May 21, 2015
BACKGROUND: The purpose of this work was to explore the systematic molecular mechanism of lung adenocarcinoma and gain a deeper insight into it.
Gene Expression Regulation, Neoplastic
Membrane Proteins
Signal Transduction
Adenocarcinoma
Humans
Gene Expression Profiling
Software
Lung Neoplasms
Computational Biology
Calcium
Peroxisome Proliferator-Activated Receptors
Protein Array Analysis
Gene Ontology
Adenocarcinoma of Lung
Collagen Type X
Receptor Cross-Talk
A Machine Learning Approach to Explain Drug Selectivity to Soluble and Membrane Protein Targets.
Molecular informatics
Jan 8, 2015
Improved understanding of the forces that determine drug specificity to their targets is important for drug design and discovery, as well as for gaining knowledge about molecular recognition. Here, we present a machine learning approach that includes...
Why Protein Modifications Matter for Digestibility: The Case of Ara h 1 Peanut Allergen and Trypsin Cleavage.
Journal of agricultural and food chemistry
Aug 20, 2025
Trypsin is the principal intestinal endopeptidase and proteomics digestion tool, yet the impact of protein modifications (PMs) on digestibility and allergenicity remains underexplored. We employed a proteomic approach to assess trypsin cleavage effic...
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