AIMC Topic: Amino Acids

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Toward Building Protein Force Fields by Residue-Based Systematic Molecular Fragmentation and Neural Network.

Journal of chemical theory and computation Jan 7, 2019
Accurate force fields are crucial for molecular dynamics investigation of complex biological systems. Building accurate protein force fields from quantum mechanical (QM) calculations is challenging due to the complexity of proteins and high computati...
Neural Networks, Computer Peptides Proteins Quantum Theory Dipeptides Static Electricity Thermodynamics Models, Chemical Amino Acids Molecular Dynamics Simulation
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Potential identification of vitamin B6 responsiveness in autism spectrum disorder utilizing phenotype variables and machine learning methods.

Scientific reports Oct 4, 2018
We investigated whether machine learning methods could potentially identify a subgroup of persons with autism spectrum disorder (ASD) who show vitamin B6 responsiveness by selected phenotype variables. We analyzed the existing data from our intervent...
Vitamin B 6 Humans Machine Learning Phenotype Male Autism Spectrum Disorder Child Female Cluster Analysis Principal Component Analysis Amino Acids
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DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning.

Genomics, proteomics & bioinformatics Sep 27, 2018
Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are...
Internet Amino Acid Sequence Nitrosation Reproducibility of Results Deep Learning Humans Proteins Neural Networks, Computer Amino Acids Software
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KELM-CPPpred: Kernel Extreme Learning Machine Based Prediction Model for Cell-Penetrating Peptides.

Journal of proteome research Aug 13, 2018
Cell-penetrating peptides (CPPs) facilitate the transport of pharmacologically active molecules, such as plasmid DNA, short interfering RNA, nanoparticles, and small peptides. The accurate identification of new and unique CPPs is the initial step to ...
Humans Animals Models, Statistical Amino Acids Internet Neural Networks, Computer Machine Learning Software Cell Membrane Permeability Cell-Penetrating Peptides Sequence Analysis, Protein Eukaryotic Cells Benchmarking Amino Acid Sequence Datasets as Topic
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A New Method for Recognizing Cytokines Based on Feature Combination and a Support Vector Machine Classifier.

Molecules (Basel, Switzerland) Aug 11, 2018
Research on cytokine recognition is of great significance in the medical field due to the fact cytokines benefit the diagnosis and treatment of diseases, but the current methods for cytokine recognition have many shortcomings, such as low sensitivity...
Databases, Protein Amino Acids Protein Structure, Secondary Sensitivity and Specificity Computational Biology Support Vector Machine Cytokines Reproducibility of Results Humans Algorithms
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Machine-Learning-Based Prediction of Cell-Penetrating Peptides and Their Uptake Efficiency with Improved Accuracy.

Journal of proteome research Jul 2, 2018
Cell-penetrating peptides (CPPs) can enter cells as a variety of biologically active conjugates and have various biomedical applications. To offset the cost and effort of designing novel CPPs in laboratories, computational methods are necessitated to...
Animals Drug Design Computational Biology Amino Acids Humans Models, Theoretical Cell-Penetrating Peptides Machine Learning Support Vector Machine
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PrESOgenesis: A two-layer multi-label predictor for identifying fertility-related proteins using support vector machine and pseudo amino acid composition approach.

Scientific reports Jun 13, 2018
Successful spermatogenesis and oogenesis are the two genetically independent processes preceding embryo development. To date, several fertility-related proteins have been described in mammalian species. Nevertheless, further studies are required to d...
Algorithms Female Reproducibility of Results Computational Biology Support Vector Machine Animals Spermatogenesis Humans Proteins Male Oogenesis Software Amino Acids Fertility
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DPP-PseAAC: A DNA-binding protein prediction model using Chou's general PseAAC.

Journal of theoretical biology May 16, 2018
A DNA-binding protein (DNA-BP) is a protein that can bind and interact with a DNA. Identification of DNA-BPs using experimental methods is expensive as well as time consuming. As such, fast and accurate computational methods are sought for predicting...
Models, Molecular Nucleic Acid Conformation Algorithms Support Vector Machine Protein Domains Reproducibility of Results DNA-Binding Proteins Amino Acids Databases, Protein Computational Biology Amino Acid Sequence DNA
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RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

BMC bioinformatics May 8, 2018
BACKGROUND: Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary...
Databases, Protein Amino Acids Software Costs and Cost Analysis Deep Learning Protein Structure, Tertiary Entropy Cluster Analysis Proteins
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Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC.

Journal of theoretical biology May 1, 2018
This study examines accurate and efficient computational method for identification of 5-methylcytosine sites in RNA modification. The occurrence of 5-methylcytosine (mC) plays a vital role in a number of biological processes. For better comprehension...
Base Sequence 5-Methylcytosine Amino Acid Sequence Models, Theoretical RNA Support Vector Machine High-Throughput Nucleotide Sequencing Proteins Humans Amino Acids Algorithms
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