AIMC Topic: Phosphoproteins

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Using support vector machines to identify protein phosphorylation sites in viruses.

Journal of molecular graphics & modelling Dec 24, 2014
Phosphorylation of viral proteins plays important roles in enhancing replication and inhibition of normal host-cell functions. Given its importance in biology, a unique opportunity has arisen to identify viral protein phosphorylation sites. However, ...
Support Vector Machine Databases, Protein Phosphorylation Phosphoproteins Amino Acid Sequence Tyrosine Viral Proteins Serine Molecular Sequence Data Protein Structure, Tertiary Threonine
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Inter-species pathway perturbation prediction via data-driven detection of functional homology.

Bioinformatics (Oxford, England) Aug 22, 2014
MOTIVATION: Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER ...
Humans Artificial Intelligence Software Algorithms Cells, Cultured Cytokines Databases, Factual Animals Gene Expression Profiling Systems Biology Rats Signal Transduction Epithelial Cells Phosphorylation Translational Research, Biomedical Phosphoproteins Gene Expression Regulation Models, Animal Species Specificity Oligonucleotide Array Sequence Analysis Bronchi
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MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction.

Bioinformatics (Oxford, England) Dec 15, 2017
MOTIVATION: Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. ...
Neural Networks, Computer Machine Learning Software Proteins Phosphorylation Phosphoproteins Protein Kinases Sequence Analysis, Protein
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RLIMS-P 2.0: A Generalizable Rule-Based Information Extraction System for Literature Mining of Protein Phosphorylation Information.

IEEE/ACM transactions on computational biology and bioinformatics Jan 1, 2015
We introduce RLIMS-P version 2.0, an enhanced rule-based information extraction (IE) system for mining kinase, substrate, and phosphorylation site information from scientific literature. Consisting of natural language processing and IE modules, the s...
Software Computational Biology Databases, Protein Phosphorylation Natural Language Processing Phosphoproteins Data Mining
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