AI Medical Compendium Topic:
Databases, Protein

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Factors analysis of protein O-glycosylation site prediction.

Computational biology and chemistry
To improve the prediction accuracy of O-glycosylation sites, and analyze the structure of the O-glycosylation sites, factor analysis based prediction is proposed in this study. Our studies show that factor analysis strongly boosts machine learning al...

Convex-PL: a novel knowledge-based potential for protein-ligand interactions deduced from structural databases using convex optimization.

Journal of computer-aided molecular design
We present a novel optimization approach to train a free-shape distance-dependent protein-ligand scoring function called Convex-PL. We do not impose any functional form of the scoring function. Instead, we decompose it into a polynomial basis and ded...

Interaction prediction in structure-based virtual screening using deep learning.

Computers in biology and medicine
We introduce a deep learning architecture for structure-based virtual screening that generates fixed-sized fingerprints of proteins and small molecules by applying learnable atom convolution and softmax operations to each molecule separately. These f...

EPuL: An Enhanced Positive-Unlabeled Learning Algorithm for the Prediction of Pupylation Sites.

Molecules (Basel, Switzerland)
Protein pupylation is a type of post-translation modification, which plays a crucial role in cellular function of bacterial organisms in prokaryotes. To have a better insight of the mechanisms underlying pupylation an initial, but important, step is ...

Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.

International journal for numerical methods in biomedical engineering
Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, and gene expression. Accurate prediction of protein...

Prediction of N-linked glycosylation sites using position relative features and statistical moments.

PloS one
Glycosylation is one of the most complex post translation modification in eukaryotic cells. Almost 50% of the human proteome is glycosylated as glycosylation plays a vital role in various biological functions such as antigen's recognition, cell-cell ...

Protein binding hot spots prediction from sequence only by a new ensemble learning method.

Amino acids
UNLABELLED: Hot spots are interfacial core areas of binding proteins, which have been applied as targets in drug design. Experimental methods are costly in both time and expense to locate hot spot areas. Recently, in-silicon computational methods hav...

pLoc-mVirus: Predict subcellular localization of multi-location virus proteins via incorporating the optimal GO information into general PseAAC.

Gene
Knowledge of subcellular locations of proteins is crucially important for in-depth understanding their functions in a cell. With the explosive growth of protein sequences generated in the postgenomic age, it is highly demanded to develop computationa...

A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

Computers in biology and medicine
Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interact...

Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Immunology
MHC class II molecules play a fundamental role in the cellular immune system: they load short peptide fragments derived from extracellular proteins and present them on the cell surface. It is currently thought that the peptide binds lying more or les...