AIMC Topic: Proteome

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DeepPRObind: Modular Deep Learner that Accurately Predicts Structure and Disorder-Annotated Protein Binding Residues.

Journal of molecular biology Jan 5, 2023
Current sequence-based predictors of protein-binding residues (PBRs) belong to two distinct categories: structure-trained vs. intrinsic disorder-trained. Since disordered PBRs differ from structured PBRs in several ways, including ability to bind mul...
Protein Binding Computational Biology Deep Learning Amino Acids Protein Conformation Proteome Databases, Protein
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Machine Learning Modeling of Protein-intrinsic Features Predicts Tractability of Targeted Protein Degradation.

Genomics, proteomics & bioinformatics Dec 6, 2022
Targeted protein degradation (TPD) has rapidly emerged as a therapeutic modality to eliminate previously undruggable proteins by repurposing the cell's endogenous protein degradation machinery. However, the susceptibility of proteins for targeting by...
Ubiquitination Machine Learning Proteome Lysine Proteolysis
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DeepIDA: Predicting Isoform-Disease Associations by Data Fusion and Deep Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
Alternative splicing produces different isoforms from the same gene locus, it is an important mechanism for regulating gene expression and proteome diversity. Although the prediction of gene(ncRNA)-disease associations has been extensively studied, f...
Neural Networks, Computer Computational Biology Gene Ontology Proteome Alternative Splicing Protein Isoforms
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Sweat Proteomics in Cystic Fibrosis: Discovering Companion Biomarkers for Precision Medicine and Therapeutic Development.

Cells Jul 31, 2022
In clinical routine, the diagnosis of cystic fibrosis (CF) is still challenging regardless of international consensus on diagnosis guidelines and tests. For decades, the classical Gibson and Cooke test measuring sweat chloride concentration has been ...
Proteomics Proteome Cystic Fibrosis Glycosyltransferases Chlorides Biomarkers Humans Sweat Precision Medicine Cystic Fibrosis Transmembrane Conductance Regulator
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Systematic prediction of degrons and E3 ubiquitin ligase binding via deep learning.

BMC biology Jul 14, 2022
BACKGROUND: Degrons are short linear motifs, bound by E3 ubiquitin ligase to target protein substrates to be degraded by the ubiquitin-proteasome system. Mutations leading to deregulation of degron functionality disrupt control of protein abundance d...
Proteome Ubiquitin-Protein Ligases Deep Learning Proteolysis Ubiquitin
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Learning Proteome Domain Folding Using LSTMs in an Empirical Kernel Space.

Journal of molecular biology Jun 15, 2022
The recognition of protein structural folds is the starting point for protein function inference and for many structural prediction tools. We previously introduced the idea of using empirical comparisons to create a data-augmented feature space calle...
Neural Networks, Computer Algorithms Protein Folding Proteome Protein Domains
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Can Omics Biology Go Subjective because of Artificial Intelligence? A Comment on "Challenges and Opportunities for Bayesian Statistics in Proteomics" by Crook et al.

Journal of proteome research Jun 10, 2022
In their recent review ( 2022, 21 (4), 849-864), Crook et al. diligently discuss the basics (and less basics) of Bayesian modeling, survey its various applications to proteomics, and highlight its potential for the improvement of computational prote...
Computational Biology Proteomics Artificial Intelligence Proteome Bayes Theorem
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Screening membraneless organelle participants with machine-learning models that integrate multimodal features.

Proceedings of the National Academy of Sciences of the United States of America Jun 10, 2022
Protein self-assembly is one of the formation mechanisms of biomolecular condensates. However, most phase-separating systems (PS) demand multiple partners in biological conditions. In this study, we divided PS proteins into two groups according to th...
Biomolecular Condensates Proteins Phosphorylation Organelles Internet Use Machine Learning Proteome Humans
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Statistical and machine learning methods to study human CD4 T cell proteome profiles.

Immunology letters Apr 2, 2022
Mass spectrometry proteomics has become an important part of modern immunology, making major contributions to understanding protein expression levels, subcellular localizations, posttranslational modifications, and interactions in various immune cell...
Humans Proteome Machine Learning CD4-Positive T-Lymphocytes Proteomics
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AF2Complex predicts direct physical interactions in multimeric proteins with deep learning.

Nature communications Apr 1, 2022
Accurate descriptions of protein-protein interactions are essential for understanding biological systems. Remarkably accurate atomic structures have been recently computed for individual proteins by AlphaFold2 (AF2). Here, we demonstrate that the sam...
Escherichia coli Sequence Alignment Deep Learning Proteome Neural Networks, Computer
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