AIMC Topic: Proteome

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Investigation of machine learning techniques on proteomics: A comprehensive survey.

Progress in biophysics and molecular biology Sep 27, 2019
Proteomics is the extensive investigation of proteins which has empowered the recognizable proof of consistently expanding quantities of protein. Proteins are necessary part of living life form, with numerous capacities. The proteome is the complete ...
Torsion, Mechanical Proteins Databases, Protein Protein Conformation Machine Learning Computer Simulation Computational Biology Proteomics Proteome
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Deep learning extends de novo protein modelling coverage of genomes using iteratively predicted structural constraints.

Nature communications Sep 4, 2019
The inapplicability of amino acid covariation methods to small protein families has limited their use for structural annotation of whole genomes. Recently, deep learning has shown promise in allowing accurate residue-residue contact prediction even f...
Humans Algorithms Reproducibility of Results Proteome Models, Molecular Animals Protein Conformation Deep Learning Binding Sites Computational Biology Proteomics
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Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

Genome research Jun 27, 2019
A central challenge in human genomics is to understand the cellular, evolutionary, and clinical significance of genetic variants. Here, we introduce a unified population-genetic and machine-learning model, called inear llele-pecific election nferenc ...
Polymorphism, Single Nucleotide Proteome Models, Genetic Alleles Autism Spectrum Disorder Neoplasms Genomics Selection, Genetic Genetics, Population Inheritance Patterns Genetic Fitness Genetic Variation Base Sequence Genome, Human Humans Machine Learning
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Machine Learning Applied to Predicting Microorganism Growth Temperatures and Enzyme Catalytic Optima.

ACS synthetic biology Jun 7, 2019
Enzymes that catalyze chemical reactions at high temperatures are used for industrial biocatalysis, applications in molecular biology, and as highly evolvable starting points for protein engineering. The optimal growth temperature (OGT) of organisms ...
Bacterial Physiological Phenomena Protein Engineering Proteome Machine Learning Bacterial Proteins Temperature Models, Biological Bacteria Enzyme Stability
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MHCSeqNet: a deep neural network model for universal MHC binding prediction.

BMC bioinformatics May 28, 2019
BACKGROUND: Immunotherapy is an emerging approach in cancer treatment that activates the host immune system to destroy cancer cells expressing unique peptide signatures (neoepitopes). Administrations of cancer-specific neoepitopes in the form of synt...
Humans Databases, Protein Area Under Curve Models, Biological Alleles Histocompatibility Antigens Class I Peptides Protein Binding Mice Proteome Neural Networks, Computer Software Animals
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Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning.

Nature methods May 27, 2019
In mass-spectrometry-based proteomics, the identification and quantification of peptides and proteins heavily rely on sequence database searching or spectral library matching. The lack of accurate predictive models for fragment ion intensities impair...
Tandem Mass Spectrometry HEK293 Cells Saccharomyces cerevisiae Drosophila melanogaster Caenorhabditis elegans Humans Neural Networks, Computer Peptide Library Proteome Databases, Protein Peptide Fragments Software Animals Deep Learning
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Machine-Learning-Based Predictor of Human-Bacteria Protein-Protein Interactions by Incorporating Comprehensive Host-Network Properties.

Journal of proteome research Apr 22, 2019
The large-scale identification of protein-protein interactions (PPIs) between humans and bacteria remains a crucial step in systematically understanding the underlying molecular mechanisms of bacterial infection. Computational prediction approaches a...
Yersinia pestis Protein Interaction Mapping Bacillus anthracis Eukaryotic Cells Molecular Mimicry Humans Francisella tularensis Machine Learning Area Under Curve Protein Binding Gene Expression Bacterial Proteins Proteome Host-Pathogen Interactions Models, Statistical Databases, Protein
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Elucidating the druggability of the human proteome with eFindSite.

Journal of computer-aided molecular design Mar 19, 2019
Identifying the viability of protein targets is one of the preliminary steps of drug discovery. Determining the ability of a protein to bind drugs in order to modulate its function, termed the druggability, requires a non-trivial amount of time and r...
Serine Proteases Binding Sites 5-Aminolevulinate Synthetase Humans Proteome Proteins Software Supervised Machine Learning Drug Design Drug Discovery Protein Binding
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NetSurfP-2.0: Improved prediction of protein structural features by integrated deep learning.

Proteins Mar 9, 2019
The ability to predict local structural features of a protein from the primary sequence is of paramount importance for unraveling its function in absence of experimental structural information. Two main factors affect the utility of potential predict...
Protein Structure, Secondary Deep Learning Computational Biology Proteome Databases, Protein
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DeepUbi: a deep learning framework for prediction of ubiquitination sites in proteins.

BMC bioinformatics Feb 18, 2019
BACKGROUND: Protein ubiquitination occurs when the ubiquitin protein binds to a target protein residue of lysine (K), and it is an important regulator of many cellular functions, such as signal transduction, cell division, and immune reactions, in eu...
Ubiquitination Ubiquitinated Proteins Deep Learning Proteomics Humans Proteome Neural Networks, Computer Lysine Software
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