AIMC Topic: Saccharomyces cerevisiae

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Prediction of protein-protein interaction using graph neural networks.

Scientific reports May 19, 2022
Proteins are the essential biological macromolecules required to perform nearly all biological processes, and cellular functions. Proteins rarely carry out their tasks in isolation but interact with other proteins (known as protein-protein interactio...
Amino Acids Amino Acid Sequence Saccharomyces cerevisiae Humans Neural Networks, Computer Proteins
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Microbial chassis engineering drives heterologous production of complex secondary metabolites.

Biotechnology advances Apr 26, 2022
The cryptic secondary metabolite biosynthetic gene clusters (BGCs) far outnumber currently known secondary metabolites. Heterologous production of secondary metabolite BGCs in suitable chassis facilitates yield improvement and discovery of new-to-nat...
Synthetic Biology Saccharomyces cerevisiae Artificial Intelligence Metabolic Engineering Escherichia coli Polyketides Multigene Family
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Identifying Protein Subcellular Locations With Embeddings-Based node2loc.

IEEE/ACM transactions on computational biology and bioinformatics Apr 1, 2022
Identifying protein subcellular locations is an important topic in protein function prediction. Interacting proteins may share similar locations. Thus, it is imperative to infer protein subcellular locations by taking protein-protein interactions (PP...
Saccharomyces cerevisiae Humans Protein Interaction Mapping Neural Networks, Computer Proteins
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Machine learning algorithm for precise prediction of 2'-O-methylation (Nm) sites from experimental RiboMethSeq datasets.

Methods (San Diego, Calif.) Mar 18, 2022
Analysis of epitranscriptomic RNA modifications by deep sequencing-based approaches brings an essential contribution to the general knowledge on their precise locations and relative stoichiometry in cellular RNAs. To reveal RNA modifications, several...
Humans Methylation Saccharomyces cerevisiae RNA, Transfer Machine Learning Algorithms RNA
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Deep Neural Network and Extreme Gradient Boosting Based Hybrid Classifier for Improved Prediction of Protein-Protein Interaction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 3, 2022
Understanding the behavioral process of life and disease-causing mechanism, knowledge regarding protein-protein interactions (PPI) is essential. In this paper, a novel hybrid approach combining deep neural network (DNN) and extreme gradient boosting ...
Humans Saccharomyces cerevisiae Protein Interaction Mapping Neural Networks, Computer Software Amino Acids
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Computed structures of core eukaryotic protein complexes.

Science (New York, N.Y.) Dec 10, 2021
Protein-protein interactions play critical roles in biology, but the structures of many eukaryotic protein complexes are unknown, and there are likely many interactions not yet identified. We take advantage of advances in proteome-wide amino acid coe...
Chromosome Segregation Ligases Multiprotein Complexes Acyltransferases Homologous Recombination Ubiquitin Protein Interaction Mapping Saccharomyces cerevisiae Proteins DNA Repair Protein Biosynthesis Ribosomes Models, Molecular Protein Conformation Saccharomyces cerevisiae Membrane Proteins Evolution, Molecular Computer Simulation Protein Interaction Maps Deep Learning Computational Biology Proteome
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Yeast cell segmentation in microstructured environments with deep learning.

Bio Systems Oct 9, 2021
Cell segmentation is a major bottleneck in extracting quantitative single-cell information from microscopy data. The challenge is exasperated in the setting of microstructured environments. While deep learning approaches have proven useful for genera...
Neural Networks, Computer Deep Learning Microscopy Saccharomyces cerevisiae
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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...
Saccharomyces cerevisiae Neural Networks, Computer Proteins Amino Acid Sequence Humans
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Protein Abundance Prediction Through Machine Learning Methods.

Journal of molecular biology Sep 23, 2021
Proteins are responsible for most physiological processes, and their abundance provides crucial information for systems biology research. However, absolute protein quantification, as determined by mass spectrometry, still has limitations in capturing...
Codon Usage Saccharomyces cerevisiae Proteins Computational Biology Protein Biosynthesis Enzymes Escherichia coli Schizosaccharomyces Biological Evolution Saccharomyces cerevisiae Machine Learning Kluyveromyces Algorithms
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Genetic dissection of complex traits using hierarchical biological knowledge.

PLoS computational biology Sep 17, 2021
Despite the growing constellation of genetic loci linked to common traits, these loci have yet to account for most heritable variation, and most act through poorly understood mechanisms. Recent machine learning (ML) systems have used hierarchical bio...
Chromosome Mapping Multifactorial Inheritance Benomyl Nucleotidyltransferases Saccharomyces cerevisiae Gene Ontology Hydroxyurea Glucose Glycine Knowledge Bases Phenotype Genome-Wide Association Study Polymorphism, Single Nucleotide Metabolic Networks and Pathways Copper Neural Networks, Computer Computational Biology Mutation Machine Learning Systems Biology Models, Genetic
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