AIMC Topic: Proteins

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Improve hot region prediction by analyzing different machine learning algorithms.

BMC bioinformatics Oct 25, 2021
BACKGROUND: In the process of designing drugs and proteins, it is crucial to recognize hot regions in protein-protein interactions. Each hot region of protein-protein interaction is composed of at least three hot spots, which play an important role i...
Cluster Analysis Bayes Theorem Support Vector Machine Proteins Algorithms Machine Learning
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Predicting subcellular location of protein with evolution information and sequence-based deep learning.

BMC bioinformatics Oct 22, 2021
BACKGROUND: Protein subcellular localization prediction plays an important role in biology research. Since traditional methods are laborious and time-consuming, many machine learning-based prediction methods have been proposed. However, most of the p...
Databases, Protein Position-Specific Scoring Matrices Amino Acid Sequence Computational Biology Proteins Deep Learning
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Protein function prediction using functional inter-relationship.

Computational biology and chemistry Oct 16, 2021
With the growth of high throughput sequencing techniques, the generation of protein sequences has become fast and cheap, leading to a huge increase in the number of known proteins. However, it is challenging to identify the functions being performed ...
Machine Learning Databases, Protein Proteins
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Improving Structure-Based Virtual Screening with Ensemble Docking and Machine Learning.

Journal of chemical information and modeling Oct 15, 2021
One of the main challenges of structure-based virtual screening (SBVS) is the incorporation of the receptor's flexibility, as its explicit representation in every docking run implies a high computational cost. Therefore, a common alternative to inclu...
Molecular Docking Simulation Protein Binding Machine Learning Protein Conformation Ligands Proteins
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prPred-DRLF: Plant R protein predictor using deep representation learning features.

Proteomics Oct 14, 2021
Plant resistance (R) proteins play a significant role in the detection of pathogen invasion. Accurately predicting plant R proteins is a key task in phytopathology. Most plant R protein predictors are dependent on traditional feature extraction metho...
Proteins Machine Learning
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FoldHSphere: deep hyperspherical embeddings for protein fold recognition.

BMC bioinformatics Oct 12, 2021
BACKGROUND: Current state-of-the-art deep learning approaches for protein fold recognition learn protein embeddings that improve prediction performance at the fold level. However, there still exists aperformance gap at the fold level and the (relativ...
Neural Networks, Computer Proteins Algorithms
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Genetic variant effect prediction by supervised nonnegative matrix tri-factorization.

Molecular omics Oct 11, 2021
Discriminating between deleterious and neutral mutations among numerous non-synonymous single nucleotide variants (nsSNVs) that may be observed through whole exome sequencing (WES) is considered a great challenge. In this regard, many machine learnin...
Machine Learning Proteins Phenotype Amino Acid Sequence Algorithms
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AoP-LSE: Antioxidant Proteins Classification Using Deep Latent Space Encoding of Sequence Features.

Current issues in molecular biology Oct 9, 2021
It is of utmost importance to develop a computational method for accurate prediction of antioxidants, as they play a vital role in the prevention of several diseases caused by oxidative stress. In this correspondence, we present an effective computat...
Antioxidants Databases, Protein Proteins Algorithms Humans Computational Biology Neural Networks, Computer Software Workflow
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Protein-protein interaction prediction based on ordinal regression and recurrent convolutional neural networks.

BMC bioinformatics Oct 8, 2021
BACKGROUND: Protein protein interactions (PPIs) are essential to most of the biological processes. The prediction of PPIs is beneficial to the understanding of protein functions and thus is helpful to pathological analysis, disease diagnosis and drug...
Proteins Neural Networks, Computer Humans Saccharomyces cerevisiae Amino Acid Sequence
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Protein Family Classification from Scratch: A CNN Based Deep Learning Approach.

IEEE/ACM transactions on computational biology and bioinformatics Oct 8, 2021
Next-generation sequencing techniques provide us with an opportunity for generating sequenced proteins and identifying the biological families and functions of these proteins. However, compared with identified proteins, uncharacterized proteins consi...
Sequence Analysis, Protein Amino Acid Sequence Computational Biology Humans Cluster Analysis Algorithms Proteins Deep Learning
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