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Sequence Analysis, Protein

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NovoRank: Refinement for Peptide Sequencing Based on Spectral Clustering and Deep Learning.

Journal of proteome research
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...

[AcidBasePred: a protein acid-base tolerance prediction platform based on deep learning].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
The structures and activities of enzymes are influenced by pH of the environment. Understanding and distinguishing the adaptation mechanisms of enzymes to extreme pH values is of great significance for elucidating the molecular mechanisms and promoti...

Deep Learning Approaches for the Prediction of Protein Functional Sites.

Molecules (Basel, Switzerland)
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...

π-PrimeNovo: an accurate and efficient non-autoregressive deep learning model for de novo peptide sequencing.

Nature communications
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...

MEGA-GO: functions prediction of diverse protein sequence length using Multi-scalE Graph Adaptive neural network.

Bioinformatics (Oxford, England)
MOTIVATION: The increasing accessibility of large-scale protein sequences through advanced sequencing technologies has necessitated the development of efficient and accurate methods for predicting protein function. Computational prediction models hav...

Generative AI Models for the Protein Scaffold Filling Problem.

Journal of computational biology : a journal of computational molecular cell biology
De novo protein sequencing is an important problem in proteomics, playing a crucial role in understanding protein functions, drug discovery, design and evolutionary studies, etc. Top-down and bottom-up tandem mass spectrometry are popular approaches ...

Deep-ProBind: binding protein prediction with transformer-based deep learning model.

BMC bioinformatics
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...

GRATCR: Epitope-Specific T Cell Receptor Sequence Generation With Data-Efficient Pre-Trained Models.

IEEE journal of biomedical and health informatics
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...

The AI revolution comes to protein sequencing.

Science (New York, N.Y.)
By identifying unknown proteins, new systems could aid research in many areas.

TransBind allows precise detection of DNA-binding proteins and residues using language models and deep learning.

Communications biology
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...