AIMC Topic: Sequence Analysis, Protein

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ECO, the Evidence & Conclusion Ontology: community standard for evidence information.

Nucleic acids research Jan 8, 2019
The Evidence and Conclusion Ontology (ECO) contains terms (classes) that describe types of evidence and assertion methods. ECO terms are used in the process of biocuration to capture the evidence that supports biological assertions (e.g. gene product...
Gene Ontology Sequence Analysis, Protein Internet Information Storage and Retrieval Animals User-Computer Interface Humans Databases, Genetic Computational Biology Proteins
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UniProt: a worldwide hub of protein knowledge.

Nucleic acids research Jan 8, 2019
The UniProt Knowledgebase is a collection of sequences and annotations for over 120 million proteins across all branches of life. Detailed annotations extracted from the literature by expert curators have been collected for over half a million of the...
Proteome Molecular Sequence Annotation Data Curation Databases, Protein Sequence Analysis, Protein Knowledge Bases
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Deep learning improves antimicrobial peptide recognition.

Bioinformatics (Oxford, England) Aug 15, 2018
MOTIVATION: Bacterial resistance to antibiotics is a growing concern. Antimicrobial peptides (AMPs), natural components of innate immunity, are popular targets for developing new drugs. Machine learning methods are now commonly adopted by wet-laborat...
Anti-Infective Agents Peptides Computational Biology Sequence Analysis, Protein Deep Learning
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Learned protein embeddings for machine learning.

Bioinformatics (Oxford, England) Aug 1, 2018
MOTIVATION: Machine-learning models trained on protein sequences and their measured functions can infer biological properties of unseen sequences without requiring an understanding of the underlying physical or biological mechanisms. Such models enab...
Sequence Analysis, Protein Computational Biology Proteins Amino Acid Sequence Eukaryota Models, Biological Software Bacteria Humans Machine Learning
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CoABind: a novel algorithm for Coenzyme A (CoA)- and CoA derivatives-binding residues prediction.

Bioinformatics (Oxford, England) Aug 1, 2018
MOTIVATION: Coenzyme A (CoA)-protein binding plays an important role in various cellular functions and metabolic pathways. However, no computational methods can be employed for CoA-binding residues prediction.
Protein Binding Computational Biology Support Vector Machine Software Bacterial Proteins Protein Conformation Sequence Analysis, Protein Proteins Models, Molecular Coenzyme A Vibrio cholerae Acetyltransferases
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SECLAF: a webserver and deep neural network design tool for hierarchical biological sequence classification.

Bioinformatics (Oxford, England) Jul 15, 2018
SUMMARY: Artificial intelligence tools are gaining more and more ground each year in bioinformatics. Learning algorithms can be taught for specific tasks by using the existing enormous biological databases, and the resulting models can be used for th...
Neural Networks, Computer Internet Gene Ontology Computational Biology Sequence Analysis, Protein Proteins
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Protein threading using residue co-variation and deep learning.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: Template-based modeling, including homology modeling and protein threading, is a popular method for protein 3D structure prediction. However, alignment generation and template selection for protein sequences without close templates remain...
Sequence Analysis, Protein Protein Structure, Secondary Sequence Alignment Deep Learning Proteins Models, Molecular Software
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DeepFam: deep learning based alignment-free method for protein family modeling and prediction.

Bioinformatics (Oxford, England) Jul 1, 2018
MOTIVATION: A large number of newly sequenced proteins are generated by the next-generation sequencing technologies and the biochemical function assignment of the proteins is an important task. However, biological experiments are too expensive to cha...
Deep Learning Proteins Sequence Analysis, Protein Receptors, G-Protein-Coupled Software
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DeepSig: deep learning improves signal peptide detection in proteins.

Bioinformatics (Oxford, England) May 15, 2018
MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.
Protein Transport Eukaryota Sequence Analysis, Protein Bacteria Protein Sorting Signals Software Internet Deep Learning
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Protein classification using modified n-grams and skip-grams.

Bioinformatics (Oxford, England) May 1, 2018
MOTIVATION: Classification by supervised machine learning greatly facilitates the annotation of protein characteristics from their primary sequence. However, the feature generation step in this process requires detailed knowledge of attributes used t...
Protein Conformation Models, Molecular Proteins Sequence Analysis, Protein Supervised Machine Learning Natural Language Processing Molecular Sequence Annotation
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