AIMC Topic: Sequence Analysis, Protein

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Variable Length Character N-Gram Embedding of Protein Sequences for Secondary Structure Prediction.

Protein and peptide letters Jan 1, 2021
BACKGROUND: The prediction of a protein's secondary structure from its amino acid sequence is an essential step towards predicting its 3-D structure. The prediction performance improves by incorporating homologous multiple sequence alignment informat...
Sequence Analysis, Protein Deep Learning Proteins Databases, Protein Protein Structure, Secondary
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Improved Prediction of Protein-Protein Interaction Mapping on by Using Amino Acid Sequence Features in a Supervised Learning Framework.

Protein and peptide letters Jan 1, 2021
BACKGROUND: Protein-Protein Interaction (PPI) has emerged as a key role in the control of many biological processes including protein function, disease incidence, and therapy design. However, the identification of PPI by wet lab experiment is a chall...
Protein Interaction Maps Computational Biology Humans Amino Acid Sequence Protein Interaction Mapping Sequence Analysis, Protein Support Vector Machine Proteins
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FastSK: fast sequence analysis with gapped string kernels.

Bioinformatics (Oxford, England) Dec 30, 2020
MOTIVATION: Gapped k-mer kernels with support vector machines (gkm-SVMs) have achieved strong predictive performance on regulatory DNA sequences on modestly sized training sets. However, existing gkm-SVM algorithms suffer from slow kernel computation...
Software Proteins Sequence Analysis, Protein Algorithms Support Vector Machine
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MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization.

Nucleic acids research Jul 2, 2020
MusiteDeep is an online resource providing a deep-learning framework for protein post-translational modification (PTM) site prediction and visualization. The predictor only uses protein sequences as input and no complex features are needed, which res...
Proteins Models, Molecular Deep Learning Protein Processing, Post-Translational Computer Graphics Sequence Analysis, Protein Internet Protein Conformation Software
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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...
Sequence Analysis, Protein CRISPR-Associated Protein 9 Prophages Bacterial Proteins Streptococcus Machine Learning Proteome
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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....
Software Algorithms Sequence Alignment Sequence Analysis, Protein 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...
Databases, Protein Support Vector Machine Humans Amino Acid Sequence Proteins Antioxidants Principal Component Analysis Sequence Analysis, Protein
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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...
Computational Biology Proteins Protein Conformation Deep Learning Sequence Analysis, Protein Protein Interaction Maps
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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...
Sequence Analysis, Protein Game Theory Proteins Amino Acid Sequence Neural Networks, Computer Deep Learning Support Vector Machine
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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...
Neural Networks, Computer Algorithms Computational Biology Proteins Metagenome Sequence Alignment Sequence Analysis, Protein
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