AIMC Topic: Sequence Analysis, Protein

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Improving Antifreeze Proteins Prediction With Protein Language Models and Hybrid Feature Extraction Networks.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Accurate identification of antifreeze proteins (AFPs) is crucial in developing biomimetic synthetic anti-icing materials and low-temperature organ preservation materials. Although numerous machine learning-based methods have been proposed for AFPs pr...
Neural Networks, Computer Algorithms Databases, Protein Sequence Analysis, Protein Antifreeze Proteins Deep Learning Computational Biology
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Bi-SeqCNN: A Novel Light-Weight Bi-Directional CNN Architecture for Protein Function Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 10, 2024
Deep learning approaches, such as convolution neural networks (CNNs) and deep recurrent neural networks (RNNs), have been the backbone for predicting protein function, with promising state-of-the-art (SOTA) results. RNNs with an in-built ability (i) ...
Databases, Protein Sequence Analysis, Protein Neural Networks, Computer Computational Biology Deep Learning Algorithms Proteins
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Generative AI Models for the Protein Scaffold Filling Problem.

Journal of computational biology : a journal of computational molecular cell biology Oct 23, 2024
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 ...
Humans Databases, Protein Artificial Intelligence Computational Biology Algorithms Proteomics Amino Acid Sequence Proteins Sequence Analysis, Protein
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DeepDBS: Identification of DNA-binding sites in protein sequences by using deep representations and random forest.

Methods (San Diego, Calif.) Sep 11, 2024
Interactions of biological molecules in organisms are considered to be primary factors for the lifecycle of that organism. Various important biological functions are dependent on such interactions and among different kinds of interactions, the protei...
Sequence Analysis, Protein DNA Random Forest Amino Acid Sequence Binding Sites DNA-Binding Proteins Protein Binding Computational Biology Databases, Protein Algorithms Deep Learning Neural Networks, Computer
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PCP-GC-LM: single-sequence-based protein contact prediction using dual graph convolutional neural network and convolutional neural network.

BMC bioinformatics Sep 2, 2024
BACKGROUND: Recently, the process of evolution information and the deep learning network has promoted the improvement of protein contact prediction methods. Nevertheless, still remain some bottleneck: (1) One of the bottlenecks is the prediction of o...
Algorithms Deep Learning Computational Biology Neural Networks, Computer Sequence Analysis, Protein Databases, Protein Protein Conformation Proteins
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Optimizing protein sequence classification: integrating deep learning models with Bayesian optimization for enhanced biological analysis.

BMC medical informatics and decision making Aug 27, 2024
Efforts to enhance the accuracy of protein sequence classification are of utmost importance in driving forward biological analyses and facilitating significant medical advancements. This study presents a cutting-edge model called ProtICNN-BiLSTM, whi...
Humans Deep Learning Proteins Bayes Theorem Computational Biology Sequence Analysis, Protein
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An end-to-end framework for the prediction of protein structure and fitness from single sequence.

Nature communications Aug 27, 2024
Significant research progress has been made in the field of protein structure and fitness prediction. Particularly, single-sequence-based structure prediction methods like ESMFold and OmegaFold achieve a balance between inference speed and prediction...
Mutation Algorithms Protein Stability Sequence Analysis, Protein Protein Conformation Models, Molecular Neural Networks, Computer Computational Biology Proteins
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PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings.

IEEE journal of biomedical and health informatics Jun 6, 2024
Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular me...
A549 Cells Amino Acid Sequence Sequence Analysis, Protein Proteins Phosphorylation Humans Deep Learning
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Application of artificial intelligence and machine learning techniques to the analysis of dynamic protein sequences.

Proteins May 29, 2024
We apply methods of Artificial Intelligence and Machine Learning to protein dynamic bioinformatics. We rewrite the sequences of a large protein data set, containing both folded and intrinsically disordered molecules, using a representation developed ...
Databases, Protein Machine Learning Amino Acid Sequence Artificial Intelligence Sequence Analysis, Protein Computational Biology Intrinsically Disordered Proteins Fourier Analysis Algorithms Proteins Protein Folding
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Sa-TTCA: An SVM-based approach for tumor T-cell antigen classification using features extracted from biological sequencing and natural language processing.

Computers in biology and medicine Apr 4, 2024
Accurately predicting tumor T-cell antigen (TTCA) sequences is a crucial task in the development of cancer vaccines and immunotherapies. TTCAs derived from tumor cells, are presented to immune cells (T cells) through major histocompatibility complex ...
Natural Language Processing Computational Biology Humans Sequence Analysis, Protein Neoplasms Antigens, Neoplasm Support Vector Machine
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