AIMC Topic: Sequence Analysis, Protein

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

Bioinformatics (Oxford, England) Feb 4, 2025
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...
Sequence Analysis, Protein Amino Acid Sequence Gene Ontology Algorithms Computational Biology Proteins Neural Networks, Computer Databases, Protein
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A fast (CNN + MCWS-transformer) based architecture for protein function prediction.

Statistical applications in genetics and molecular biology Jan 1, 2025
The transformer model for sequence mining has brought a paradigmatic shift to many domains, including biological sequence mining. However, transformers suffer from quadratic complexity, i.e., O( ), where is the sequence length, which affects the tra...
Neural Networks, Computer Proteins Databases, Protein Sequence Analysis, Protein Algorithms Computational Biology
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[AcidBasePred: a protein acid-base tolerance prediction platform based on deep learning].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology Dec 25, 2024
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...
Proteins Bacterial Proteins Hydrogen-Ion Concentration Deep Learning Sequence Analysis, Protein Amino Acid Sequence Enzymes
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Deep learning for the PSIPRED Protein Analysis Workbench.

Nucleic acids research Jul 5, 2024
The PSIRED Workbench is a long established and popular bioinformatics web service offering a wide range of machine learning based analyses for characterizing protein structure and function. In this paper we provide an update of the recent additions a...
Internet Protein Conformation Computational Biology Proteins Sequence Analysis, Protein Software Deep Learning
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Effect of tokenization on transformers for biological sequences.

Bioinformatics (Oxford, England) Mar 29, 2024
MOTIVATION: Deep-learning models are transforming biological research, including many bioinformatics and comparative genomics algorithms, such as sequence alignments, phylogenetic tree inference, and automatic classification of protein functions. Amo...
Sequence Analysis, Protein Deep Learning Computational Biology Algorithms Natural Language Processing Proteins Sequence Alignment
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DeepSS2GO: protein function prediction from secondary structure.

Briefings in bioinformatics Mar 27, 2024
Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets. In recent years, methods based on sequence, structure and biological networks for protein function annotation hav...
Algorithms Computational Biology Proteins Databases, Protein Sequence Analysis, Protein Neural Networks, Computer Software Gene Ontology Protein Structure, Secondary
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SPDesign: protein sequence designer based on structural sequence profile using ultrafast shape recognition.

Briefings in bioinformatics Mar 27, 2024
Protein sequence design can provide valuable insights into biopharmaceuticals and disease treatments. Currently, most protein sequence design methods based on deep learning focus on network architecture optimization, while ignoring protein-specific p...
Sequence Alignment Sequence Analysis, Protein Proteins Neural Networks, Computer Amino Acid Sequence
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MMSMAPlus: a multi-view multi-scale multi-attention embedding model for protein function prediction.

Briefings in bioinformatics Jul 20, 2023
Protein is the most important component in organisms and plays an indispensable role in life activities. In recent years, a large number of intelligent methods have been proposed to predict protein function. These methods obtain different types of pr...
Amino Acid Sequence Neural Networks, Computer Sequence Analysis, Protein Software Proteins
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Illuminating the "Twilight Zone": Advances in Difficult Protein Modeling.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Homology modeling was long considered a method of choice in tertiary protein structure prediction. However, it used to provide models of acceptable quality only when templates with appreciable sequence identity with a target could be found. The thres...
Protein Conformation Protein Folding Proteins Databases, Protein Protein Structure, Tertiary Sequence Analysis, Protein Machine Learning Computational Biology
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DistilProtBert: a distilled protein language model used to distinguish between real proteins and their randomly shuffled counterparts.

Bioinformatics (Oxford, England) Sep 16, 2022
SUMMARY: Recently, deep learning models, initially developed in the field of natural language processing (NLP), were applied successfully to analyze protein sequences. A major drawback of these models is their size in terms of the number of parameter...
Amino Acid Sequence Sequence Analysis, Protein Natural Language Processing Humans Proteome Amino Acids
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