AIMC Topic: Sequence Analysis, Protein

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Machine learning predicts new anti-CRISPR proteins.

Nucleic acids research May 21, 2020
The increasing use of CRISPR-Cas9 in medicine, agriculture, and synthetic biology has accelerated the drive to discover new CRISPR-Cas inhibitors as potential mechanisms of control for gene editing applications. Many anti-CRISPRs have been found that...
Machine Learning Sequence Analysis, Protein CRISPR-Associated Protein 9 Prophages Proteome Bacterial Proteins Streptococcus
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DeepMSA: constructing deep multiple sequence alignment to improve contact prediction and fold-recognition for distant-homology proteins.

Bioinformatics (Oxford, England) Apr 1, 2020
MOTIVATION: The success of genome sequencing techniques has resulted in rapid explosion of protein sequences. Collections of multiple homologous sequences can provide critical information to the modeling of structure and function of unknown proteins....
Sequence Alignment Sequence Analysis, Protein Software Algorithms Proteins Neural Networks, Computer
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Antioxidant Proteins' Identification Based on Support Vector Machine.

Combinatorial chemistry & high throughput screening Jan 1, 2020
BACKGROUND: Evidence have increasingly indicated that for human disease, cell metabolism are deeply associated with proteins. Structural mutations and dysregulations of these proteins contribute to the development of the complex disease. Free radical...
Sequence Analysis, Protein Antioxidants Support Vector Machine Proteins Databases, Protein Principal Component Analysis Amino Acid Sequence Humans
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A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
Identifying residue-residue contacts in protein-protein interactions or complex is crucial for understanding protein and cell functions. DCA (direct-coupling analysis) methods shed some light on this, but they need many sequence homologs to yield acc...
Protein Interaction Maps Computational Biology Proteins Deep Learning Protein Conformation Sequence Analysis, Protein
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Deep learning on chaos game representation for proteins.

Bioinformatics (Oxford, England) Jan 1, 2020
MOTIVATION: Classification of protein sequences is one big task in bioinformatics and has many applications. Different machine learning methods exist and are applied on these problems, such as support vector machines (SVM), random forests (RF) and ne...
Deep Learning Support Vector Machine Proteins Neural Networks, Computer Game Theory Amino Acid Sequence Sequence Analysis, Protein
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Protein contact prediction using metagenome sequence data and residual neural networks.

Bioinformatics (Oxford, England) Jan 1, 2020
MOTIVATION: Almost all protein residue contact prediction methods rely on the availability of deep multiple sequence alignments (MSAs). However, many proteins from the poorly populated families do not have sufficient number of homologs in the convent...
Computational Biology Proteins Sequence Alignment Sequence Analysis, Protein Metagenome Neural Networks, Computer Algorithms
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Machine learning-based chemical binding similarity using evolutionary relationships of target genes.

Nucleic acids research Nov 18, 2019
Chemical similarity searching is a basic research tool that can be used to find small molecules which are similar in shape to known active molecules. Despite its popularity, the retrieval of local molecular features that are critical to functional ac...
Sequence Analysis, Protein Genes Protein Kinase Inhibitors Small Molecule Libraries Machine Learning Animals Protein Binding Evolution, Molecular Protein Kinases Quantitative Structure-Activity Relationship Humans
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BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches.

Briefings in bioinformatics Jul 19, 2019
With the avalanche of biological sequences generated in the post-genomic age, one of the most challenging problems is how to computationally analyze their structures and functions. Machine learning techniques are playing key roles in this field. Typi...
Machine Learning Software Algorithms Computational Biology Sequence Analysis, RNA Sequence Analysis, DNA Humans Sequence Analysis, Protein Sequence Analysis Databases, Protein Internet Databases, Nucleic Acid
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NetGO: improving large-scale protein function prediction with massive network information.

Nucleic acids research Jul 2, 2019
Automated function prediction (AFP) of proteins is of great significance in biology. AFP can be regarded as a problem of the large-scale multi-label classification where a protein can be associated with multiple gene ontology terms as its labels. Bas...
Sequence Analysis, Protein Prokaryotic Cells Sequence Alignment Sequence Homology, Amino Acid Structure-Activity Relationship Humans Models, Molecular Machine Learning Molecular Sequence Annotation Internet Software Gene Ontology Proteins Animals Benchmarking Protein Interaction Mapping Databases, Protein Computational Biology Plants Amino Acid Sequence
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BIPSPI: a method for the prediction of partner-specific protein-protein interfaces.

Bioinformatics (Oxford, England) Feb 1, 2019
MOTIVATION: Protein-Protein Interactions (PPI) are essentials for most cellular processes and thus, unveiling how proteins interact is a crucial question that can be better understood by identifying which residues are responsible for the interaction....
Proteins Machine Learning Sequence Analysis, Protein Protein Domains Protein Interaction Maps Binding Sites
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