AI Medical Compendium Topic:
Amino Acid Sequence

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Subcellular localization prediction of apoptosis proteins based on evolutionary information and support vector machine.

Artificial intelligence in medicine
OBJECTIVES: In this paper, a high-quality sequence encoding scheme is proposed for predicting subcellular location of apoptosis proteins.

Membrane protein contact and structure prediction using co-evolution in conjunction with machine learning.

PloS one
De novo membrane protein structure prediction is limited to small proteins due to the conformational search space quickly expanding with length. Long-range contacts (24+ amino acid separation)-residue positions distant in sequence, but in close proxi...

Investigating Correlation between Protein Sequence Similarity and Semantic Similarity Using Gene Ontology Annotations.

IEEE/ACM transactions on computational biology and bioinformatics
Sequence similarity is a commonly used measure to compare proteins. With the increasing use of ontologies, semantic (function) similarity is getting importance. The correlation between these measures has been applied in the evaluation of new semantic...

Amino acid composition predicts prion activity.

PLoS computational biology
Many prion-forming proteins contain glutamine/asparagine (Q/N) rich domains, and there are conflicting opinions as to the role of primary sequence in their conversion to the prion form: is this phenomenon driven primarily by amino acid composition, o...

Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

Journal of chemical information and modeling
The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pea...

Extracting features from protein sequences to improve deep extreme learning machine for protein fold recognition.

Journal of theoretical biology
Protein fold recognition is an important problem in bioinformatics to predict three-dimensional structure of a protein. One of the most challenging tasks in protein fold recognition problem is the extraction of efficient features from the amino-acid ...

InterPred: A pipeline to identify and model protein-protein interactions.

Proteins
Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the numb...

Identify and analysis crotonylation sites in histone by using support vector machines.

Artificial intelligence in medicine
OBJECTIVE: Lysine crotonylation (Kcr) is a newly discovered histone posttranslational modification, which is specifically enriched at active gene promoters and potential enhancers in mammalian cell genomes. Although lysine crotonylation sites can be ...

Improved prediction of protein-protein interactions using novel negative samples, features, and an ensemble classifier.

Artificial intelligence in medicine
Computational methods are employed in bioinformatics to predict protein-protein interactions (PPIs). PPIs and protein-protein non-interactions (PPNIs) display different levels of development, and the number of PPIs is considerably greater than that o...

HemoPred: a web server for predicting the hemolytic activity of peptides.

Future medicinal chemistry
AIM: Toxicity arising from hemolytic activity of peptides hinders its further progress as drug candidates.