AIMC Topic: Sequence Analysis, Protein

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The AI revolution comes to protein sequencing.

Science (New York, N.Y.) Apr 10, 2025
By identifying unknown proteins, new systems could aid research in many areas.
Proteins Sequence Analysis, Protein Humans Artificial Intelligence
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TransBind allows precise detection of DNA-binding proteins and residues using language models and deep learning.

Communications biology Apr 5, 2025
Identifying DNA-binding proteins and their binding residues is critical for understanding diverse biological processes, but conventional experimental approaches are slow and costly. Existing machine learning methods, while faster, often lack accuracy...
Sequence Analysis, Protein Software Deep Learning DNA-Binding Proteins Sequence Alignment Computational Biology Humans
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SeqNovo: De Novo Peptide Sequencing Prediction in IoMT via Seq2Seq.

IEEE journal of biomedical and health informatics Apr 4, 2025
In the Internet of Medical Things (IoMT), de novo peptide sequencing prediction is one of the most important techniques for the fields of disease prediction, diagnosis, and treatment. Recently, deep-learning-based peptide sequencing prediction has be...
Algorithms Peptides Deep Learning Humans Computational Biology Sequence Analysis, Protein
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Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine Mar 30, 2025
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...
Humans Neural Networks, Computer Algorithms Amino Acid Sequence Protein Conformation Sequence Analysis, Protein Proteins Deep Learning Computational Biology Protein Interaction Mapping Databases, Protein Protein Binding
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Deep-ProBind: binding protein prediction with transformer-based deep learning model.

BMC bioinformatics Mar 22, 2025
Binding proteins play a crucial role in biological systems by selectively interacting with specific molecules, such as DNA, RNA, or peptides, to regulate various cellular processes. Their ability to recognize and bind target molecules with high speci...
Neural Networks, Computer Deep Learning Protein Binding Algorithms Databases, Protein Computational Biology Binding Sites Proteins Sequence Analysis, Protein
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GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

IEEE journal of biomedical and health informatics Mar 6, 2025
T cell receptors (TCRs) play a crucial role in numerous immunotherapies targeting tumor cells. However, their acquisition and optimization present significant challenges, involving laborious and time-consuming wet lab experimental resource. Deep gene...
Epitopes, T-Lymphocyte Deep Learning Humans Computational Biology Sequence Analysis, Protein Receptors, Antigen, T-Cell
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Simpler Protein Domain Identification Using Spectral Clustering.

Proteins Feb 13, 2025
The decomposition of a biomolecular complex into domains is an important step to investigate biological functions and ease structure determination. A successful approach to do so is the SPECTRUS algorithm, which provides a segmentation based on spect...
Cluster Analysis Proteins Databases, Protein Deep Learning Computational Biology Protein Conformation Sequence Alignment Sequence Analysis, Protein Protein Domains Amino Acid Sequence Models, Molecular Algorithms
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Deep Learning Approaches for the Prediction of Protein Functional Sites.

Molecules (Basel, Switzerland) Jan 7, 2025
Knowing which residues of a protein are important for its function is of paramount importance for understanding the molecular basis of this function and devising ways of modifying it for medical or biotechnological applications. Due to the difficulty...
Databases, Protein Binding Sites Humans Sequence Analysis, Protein Deep Learning Computational Biology Proteins
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π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.

Nature communications Jan 2, 2025
Peptide sequencing via tandem mass spectrometry (MS/MS) is essential in proteomics. Unlike traditional database searches, deep learning excels at de novo peptide sequencing, even for peptides missing from existing databases. Current deep learning mod...
Phosphopeptides Databases, Protein Tandem Mass Spectrometry Sequence Analysis, Protein Algorithms Proteomics Peptides Protein Processing, Post-Translational Deep Learning Humans Software
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NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research Dec 31, 2024
peptide sequencing is a valuable technique in mass-spectrometry-based proteomics, as it deduces peptide sequences directly from tandem mass spectra without relying on sequence databases. This database-independent method, however, relies solely on im...
Databases, Protein Software Deep Learning Sequence Analysis, Protein Peptides Proteomics Tandem Mass Spectrometry Cluster Analysis
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