AIMC Topic: Protein Processing, Post-Translational

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Enhanced O-glycosylation site prediction using explainable machine learning technique with spatial local environment.

Bioinformatics (Oxford, England) Feb 4, 2025
MOTIVATION: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning (ML) models primarily relied on primary or secondary protein structural and re...
Glycosylation Protein Processing, Post-Translational Proteins Machine Learning Computational Biology Neural Networks, Computer
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Personalized treatment decision-making using a machine learning-derived lactylation signature for breast cancer prognosis.

Frontiers in immunology Jan 1, 2025
BACKGROUND: Breast cancer is a heterogeneous malignancy with complex molecular characteristics, making accurate prognostication and treatment stratification particularly challenging. Emerging evidence suggests that lactylation, a novel post-translati...
Clinical Decision-Making Female Precision Medicine Prognosis Biomarkers, Tumor Humans Lymphocytes, Tumor-Infiltrating Machine Learning Protein Processing, Post-Translational Breast Neoplasms Tumor Microenvironment
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Improved prediction of post-translational modification crosstalk within proteins using DeepPCT.

Bioinformatics (Oxford, England) Nov 28, 2024
MOTIVATION: Post-translational modification (PTM) crosstalk events play critical roles in biological processes. Several machine learning methods have been developed to identify PTM crosstalk within proteins, but the accuracy is still far from satisfa...
Databases, Protein Algorithms Deep Learning Protein Processing, Post-Translational Proteins Neural Networks, Computer Computational Biology
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Sitetack: a deep learning model that improves PTM prediction by using known PTMs.

Bioinformatics (Oxford, England) Nov 1, 2024
MOTIVATION: Post-translational modifications (PTMs) increase the diversity of the proteome and are vital to organismal life and therapeutic strategies. Deep learning has been used to predict PTM locations. Still, limitations in datasets and their ana...
Neural Networks, Computer Software Humans Proteomics Proteome Protein Processing, Post-Translational Algorithms Deep Learning Databases, Protein
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DeepPRMS: advanced deep learning model to predict protein arginine methylation sites.

Briefings in functional genomics Jul 19, 2024
Protein methylation is a form of post-translational modifications of protein, which is crucial for various cellular processes, including transcription activity and DNA repair. Correctly predicting protein methylation sites is fundamental for research...
Arginine Proteins Neural Networks, Computer Methylation Algorithms Computational Biology Humans Protein Processing, Post-Translational Deep Learning
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TransPTM: a transformer-based model for non-histone acetylation site prediction.

Briefings in bioinformatics Mar 27, 2024
Protein acetylation is one of the extensively studied post-translational modifications (PTMs) due to its significant roles across a myriad of biological processes. Although many computational tools for acetylation site identification have been develo...
Neural Networks, Computer Software Acetylation Humans Computational Biology Proteins Algorithms Databases, Protein Protein Processing, Post-Translational
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Lactylation prediction models based on protein sequence and structural feature fusion.

Briefings in bioinformatics Jan 22, 2024
Lysine lactylation (Kla) is a newly discovered posttranslational modification that is involved in important life activities, such as glycolysis-related cell function, macrophage polarization and nervous system regulation, and has received widespread ...
Protein Processing, Post-Translational Natural Language Processing Lysine Protein Domains Amino Acid Sequence
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Analysis and review of techniques and tools based on machine learning and deep learning for prediction of lysine malonylation sites in protein sequences.

Database : the journal of biological databases and curation Jan 19, 2024
The post-translational modifications occur as crucial molecular regulatory mechanisms utilized to regulate diverse cellular processes. Malonylation of proteins, a reversible post-translational modification of lysine/k residues, is linked to a variety...
Lysine Protein Processing, Post-Translational Machine Learning Proteins Deep Learning
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THPLM: a sequence-based deep learning framework for protein stability changes prediction upon point variations using pretrained protein language model.

Bioinformatics (Oxford, England) Nov 1, 2023
MOTIVATION: Quantitative determination of protein thermodynamic stability is a critical step in protein and drug design. Reliable prediction of protein stability changes caused by point variations contributes to developing-related fields. Over the pa...
Protein Processing, Post-Translational Proteins Neural Networks, Computer Software Deep Learning
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PPICT: an integrated deep neural network for predicting inter-protein PTM cross-talk.

Briefings in bioinformatics Mar 19, 2023
Post-translational modifications (PTMs) fine-tune various signaling pathways not only by the modification of a single residue, but also by the interplay of different modifications on residue pairs within or between proteins, defined as PTM cross-talk...
Protein Domains Signal Transduction Neural Networks, Computer Protein Processing, Post-Translational Proteome
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