AIMC Topic: Amino Acid Sequence

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BGFE: A Deep Learning Model for ncRNA-Protein Interaction Predictions Based on Improved Sequence Information.

International journal of molecular sciences Feb 23, 2019
The interactions between ncRNAs and proteins are critical for regulating various cellular processes in organisms, such as gene expression regulations. However, due to limitations, including financial and material consumptions in recent experimental m...
Software Deep Learning ROC Curve Amino Acid Sequence RNA, Untranslated Position-Specific Scoring Matrices Protein Binding Computational Biology Databases, Protein
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SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology Feb 18, 2019
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...
Protein Sorting Signals Archaeal Proteins Biotechnology Eukaryota Sequence Analysis, Protein Neural Networks, Computer Software Algorithms Computational Biology Bacterial Proteins Amino Acid Sequence
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PPI-Detect: A support vector machine model for sequence-based prediction of protein-protein interactions.

Journal of computational chemistry Feb 15, 2019
The prediction of peptide-protein or protein-protein interactions (PPI) is a challenging task, especially if amino acid sequences are the only information available. Machine learning methods allow us to exploit the information content in PPI datasets...
Protein Binding Databases, Protein Computational Biology Models, Chemical Amino Acid Sequence Support Vector Machine Proteins
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Integration of A Deep Learning Classifier with A Random Forest Approach for Predicting Malonylation Sites.

Genomics, proteomics & bioinformatics Jan 11, 2019
As a newly-identified protein post-translational modification, malonylation is involved in a variety of biological functions. Recognizing malonylation sites in substrates represents an initial but crucial step in elucidating the molecular mechanisms ...
Amino Acids Animals Malonates Amino Acid Sequence Deep Learning Machine Learning Lysine Protein Processing, Post-Translational Forecasting
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DeepCDpred: Inter-residue distance and contact prediction for improved prediction of protein structure.

PloS one Jan 8, 2019
Rapid, accurate prediction of protein structure from amino acid sequence would accelerate fields as diverse as drug discovery, synthetic biology and disease diagnosis. Massively improved prediction of protein structures has been driven by improving t...
Proteins Databases, Protein Models, Molecular Deep Learning Computational Biology Support Vector Machine Amino Acid Sequence Protein Structure, Tertiary Sequence Analysis, Protein Algorithms
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Classification, substrate specificity and structural features of D-2-hydroxyacid dehydrogenases: 2HADH knowledgebase.

BMC evolutionary biology Dec 22, 2018
BACKGROUND: The family of D-isomer specific 2-hydroxyacid dehydrogenases (2HADHs) contains a wide range of oxidoreductases with various metabolic roles as well as biotechnological applications. Despite a vast amount of biochemical and structural data...
Amino Acid Sequence Knowledge Bases Catalytic Domain Alcohol Oxidoreductases Likelihood Functions Substrate Specificity Phylogeny Coenzymes
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SFPEL-LPI: Sequence-based feature projection ensemble learning for predicting LncRNA-protein interactions.

PLoS computational biology Dec 11, 2018
LncRNA-protein interactions play important roles in post-transcriptional gene regulation, poly-adenylation, splicing and translation. Identification of lncRNA-protein interactions helps to understand lncRNA-related activities. Existing computational ...
RNA Processing, Post-Transcriptional RNA-Binding Proteins RNA, Long Noncoding Databases, Protein Amino Acid Sequence Base Sequence Databases, Nucleic Acid Algorithms Protein Binding Humans Computational Biology Machine Learning
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Discovering de novo peptide substrates for enzymes using machine learning.

Nature communications Dec 7, 2018
The discovery of peptide substrates for enzymes with exclusive, selective activities is a central goal in chemical biology. In this paper, we develop a hybrid computational and biochemical method to rapidly optimize peptides for specific, orthogonal ...
Bayes Theorem Bacterial Proteins Amino Acid Sequence Substrate Specificity Transferases (Other Substituted Phosphate Groups) Peptides Protein Binding Machine Learning Recombinant Proteins
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Computational discovery of direct associations between GO terms and protein domains.

BMC bioinformatics Nov 20, 2018
BACKGROUND: Families of related proteins and their different functions may be described systematically using common classifications and ontologies such as Pfam and GO (Gene Ontology), for example. However, many proteins consist of multiple domains, a...
Protein Domains Algorithms Gene Ontology Proteins Computational Biology Amino Acid Sequence Databases, Protein Molecular Sequence Annotation Area Under Curve
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Learning protein binding affinity using privileged information.

BMC bioinformatics Nov 15, 2018
BACKGROUND: Determining protein-protein interactions and their binding affinity are important in understanding cellular biological processes, discovery and design of novel therapeutics, protein engineering, and mutagenesis studies. Due to the time an...
Amino Acid Sequence Reproducibility of Results Ligands Computational Biology ROC Curve Machine Learning Support Vector Machine Protein Binding Algorithms Proteins
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