AIMC Topic: Sequence Analysis, Protein

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Identifying Cancer-Specific circRNA-RBP Binding Sites Based on Deep Learning.

Molecules (Basel, Switzerland) Nov 7, 2019
Circular RNAs (circRNAs) are extensively expressed in cells and tissues, and play crucial roles in human diseases and biological processes. Recent studies have reported that circRNAs could function as RNA binding protein (RBP) sponges, meanwhile RBPs...
RNA, Neoplasm RNA, Circular Neoplasm Proteins Binding Sites Sequence Analysis, Protein Deep Learning RNA-Binding Proteins Databases, Protein Humans Neoplasms
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Characterization and Identification of Lysine Succinylation Sites based on Deep Learning Method.

Scientific reports Nov 7, 2019
Succinylation is a type of protein post-translational modification (PTM), which can play important roles in a variety of cellular processes. Due to an increasing number of site-specific succinylated peptides obtained from high-throughput mass spectro...
Deep Learning Lysine Succinic Acid Sequence Analysis, Protein Protein Processing, Post-Translational Proteins Databases, Protein
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Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid Peptide Sequencing Framework.

Molecular & cellular proteomics : MCP Oct 7, 2019
Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpec...
Humans Peptides Phosphopeptides Tandem Mass Spectrometry Deep Learning Datasets as Topic HLA Antigens Sequence Analysis, Protein Amino Acid Sequence
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Analysis of distance-based protein structure prediction by deep learning in CASP13.

Proteins Sep 13, 2019
This paper reports the CASP13 results of distance-based contact prediction, threading, and folding methods implemented in three RaptorX servers, which are built upon the powerful deep convolutional residual neural network (ResNet) method initiated by...
Proteins Models, Molecular Crystallography, X-Ray Algorithms Deep Learning Computational Biology Sequence Analysis, Protein Protein Conformation Protein Folding Sequence Alignment Machine Learning Software
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econvRBP: Improved ensemble convolutional neural networks for RNA binding protein prediction directly from sequence.

Methods (San Diego, Calif.) Sep 9, 2019
RNA binding proteins (RBPs) determine RNA process from synthesis to decay, which play a key role in RNA transport, translation and degradation. Therefore, exploring RBPs' function from the amino acid sequence using computational methods has become on...
RNA Datasets as Topic Binding Sites Sequence Analysis, Protein Computational Biology RNA-Binding Proteins Amino Acid Sequence Deep Learning
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Boosting phosphorylation site prediction with sequence feature-based machine learning.

Proteins Aug 22, 2019
Protein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM-based computational approach that uses evolutionary, geometric, sequenc...
Humans Machine Learning Protein Conformation Algorithms Databases, Protein Threonine Species Specificity Reproducibility of Results Phosphorylation Binding Sites Tyrosine Animals Computational Biology Models, Molecular Serine Protein Processing, Post-Translational Sequence Analysis, Protein Proteins
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Single T Cell Sequencing Demonstrates the Functional Role of TCR Pairing in Cell Lineage and Antigen Specificity.

Frontiers in immunology Jul 31, 2019
Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antigen recognition, repertoire-level immunogenomic analyses have historically examined the β chain alone....
CD8-Positive T-Lymphocytes Humans Sequence Analysis, Protein CD4-Positive T-Lymphocytes Machine Learning Antigens Complementarity Determining Regions Receptors, Antigen, T-Cell, alpha-beta
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DeepConv-DTI: Prediction of drug-target interactions via deep learning with convolution on protein sequences.

PLoS computational biology Jun 14, 2019
Identification of drug-target interactions (DTIs) plays a key role in drug discovery. The high cost and labor-intensive nature of in vitro and in vivo experiments have highlighted the importance of in silico-based DTI prediction approaches. In severa...
Sequence Analysis, Protein Amino Acid Sequence Drug Discovery Ligands Deep Learning Proteins Computer Simulation Binding Sites Computational Biology Models, Molecular
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A novel matrix of sequence descriptors for predicting protein-protein interactions from amino acid sequences.

PloS one Jun 7, 2019
Protein-protein interactions (PPIs) play an important role in the life activities of organisms. With the availability of large amounts of protein sequence data, PPIs prediction methods have attracted increasing attention. A variety of protein sequenc...
Models, Genetic Databases, Protein Humans Sequence Analysis, Protein Deep Learning Protein Interaction Maps
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End-to-End Differentiable Learning of Protein Structure.

Cell systems Apr 17, 2019
Predicting protein structure from sequence is a central challenge of biochemistry. Co-evolution methods show promise, but an explicit sequence-to-structure map remains elusive. Advances in deep learning that replace complex, human-designed pipelines ...
Machine Learning Software Evolution, Molecular Protein Folding Sequence Analysis, Protein
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