AI Medical Compendium Topic:
Amino Acid Sequence

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MITNet: a fusion transformer and convolutional neural network architecture approach for T-cell epitope prediction.

Briefings in bioinformatics
Classifying epitopes is essential since they can be applied in various fields, including therapeutics, diagnostics and peptide-based vaccines. To determine the epitope or peptide against an antibody, epitope mapping with peptides is the most extensiv...

Masked Language Modeling for Resource Constrained Biological Natural Language Processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Recent advances in Natural Language Processing (NLP) have produced state of the art results on several sequence to sequence (seq2seq) tasks. Enhancements in embedders and their training methodologies have shown significant improvement on downstream t...

UniDL4BioPep: a universal deep learning architecture for binary classification in peptide bioactivity.

Briefings in bioinformatics
Identification of potent peptides through model prediction can reduce benchwork in wet experiments. However, the conventional process of model buildings can be complex and time consuming due to challenges such as peptide representation, feature selec...

PreTP-2L: identification of therapeutic peptides and their types using two-layer ensemble learning framework.

Bioinformatics (Oxford, England)
MOTIVATION: Therapeutic peptides play an important role in immune regulation. Recently various therapeutic peptides have been used in the field of medical research, and have great potential in the design of therapeutic schedules. Therefore, it is ess...

SGPPI: structure-aware prediction of protein-protein interactions in rigorous conditions with graph convolutional network.

Briefings in bioinformatics
While deep learning (DL)-based models have emerged as powerful approaches to predict protein-protein interactions (PPIs), the reliance on explicit similarity measures (e.g. sequence similarity and network neighborhood) to known interacting proteins m...

Searching and Navigating UniProt Databases.

Current protocols
The Universal Protein Resource (UniProt) is a comprehensive resource for protein sequence and annotation data. The UniProt website receives about 800,000 unique visitors per month and is the primary means to access UniProt. It provides 10 searchable ...

AFTGAN: prediction of multi-type PPI based on attention free transformer and graph attention network.

Bioinformatics (Oxford, England)
MOTIVATION: Protein-protein interaction (PPI) networks and transcriptional regulatory networks are critical in regulating cells and their signaling. A thorough understanding of PPIs can provide more insights into cellular physiology at normal and dis...

QuoteTarget: A sequence-based transformer protein language model to identify potentially druggable protein targets.

Protein science : a publication of the Protein Society
The development of efficient computational methods for drug target protein identification can compensate for the high cost of experiments and is therefore of great significance for drug development. However, existing structure-based drug target prote...

Neural network-derived Potts models for structure-based protein design using backbone atomic coordinates and tertiary motifs.

Protein science : a publication of the Protein Society
Designing novel proteins to perform desired functions, such as binding or catalysis, is a major goal in synthetic biology. A variety of computational approaches can aid in this task. An energy-based framework rooted in the sequence-structure statisti...

Integrated mRNA sequence optimization using deep learning.

Briefings in bioinformatics
The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a cri...