AIMC Topic: Amino Acid Sequence

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Numerical stability of DeepGOPlus inference.

PloS one Jan 29, 2024
Convolutional neural networks (CNNs) are currently among the most widely-used deep neural network (DNN) architectures available and achieve state-of-the-art performance for many problems. Originally applied to computer vision tasks, CNNs work well wi...
Monte Carlo Method Proteins Amino Acid Sequence Reproducibility of Results Neural Networks, Computer
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PandoGen: Generating complete instances of future SARS-CoV-2 sequences using Deep Learning.

PLoS computational biology Jan 19, 2024
One of the challenges in a viral pandemic is the emergence of novel variants with different phenotypical characteristics. An ability to forecast future viral individuals at the sequence level enables advance preparation by characterizing the sequence...
SARS-CoV-2 Spike Glycoprotein, Coronavirus Deep Learning Humans COVID-19 Amino Acid Sequence
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PPSNO: A Feature-Rich SNO Sites Predictor by Stacking Ensemble Strategy from Protein Sequence-Derived Information.

Interdisciplinary sciences, computational life sciences Jan 11, 2024
The protein S-nitrosylation (SNO) is a significant post-translational modification that affects the stability, activity, cellular localization, and function of proteins. Therefore, highly accurate prediction of SNO sites aids in grasping biological f...
Amino Acid Sequence Proteins Machine Learning Protein Processing, Post-Translational Protein Domains
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Computational Design of Peptide Assemblies.

Journal of chemical theory and computation Jan 11, 2024
With the ongoing development of peptide self-assembling materials, there is growing interest in exploring novel functional peptide sequences. From short peptides to long polypeptides, as the functionality increases, the sequence space is also expandi...
Molecular Dynamics Simulation Artificial Intelligence Proteins Peptides Amino Acid Sequence
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Mining and rational design of psychrophilic catalases using metagenomics and deep learning models.

Applied microbiology and biotechnology Jan 4, 2024
A complete catalase-encoding gene, designated soiCat1, was obtained from soil samples via metagenomic sequencing, assembly, and gene prediction. soiCat1 showed 73% identity to a catalase-encoding gene of Mucilaginibacter rubeus strain P1, and the ami...
Catalase Amino Acid Sequence Soil Amino Acids Deep Learning
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Integration of persistent Laplacian and pre-trained transformer for protein solubility changes upon mutation.

Computers in biology and medicine Jan 3, 2024
Protein mutations can significantly influence protein solubility, which results in altered protein functions and leads to various diseases. Despite tremendous effort, machine learning prediction of protein solubility changes upon mutation remains a c...
Solubility Amino Acid Sequence Mutation Machine Learning
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DL-SPhos: Prediction of serine phosphorylation sites using transformer language model.

Computers in biology and medicine Jan 3, 2024
Serine phosphorylation plays a pivotal role in the pathogenesis of various cellular processes and diseases. Roughly 81% of human diseases have links to phosphorylation, and an overwhelming 86.4% of protein phosphorylation takes place at serine residu...
Humans Proteins Phosphorylation Animals Neural Networks, Computer Mammals Serine Amino Acid Sequence
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Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing.

Nature communications Jan 2, 2024
Unlike for DNA and RNA, accurate and high-throughput sequencing methods for proteins are lacking, hindering the utility of proteomics in applications where the sequences are unknown including variant calling, neoepitope identification, and metaproteo...
Algorithms Amino Acid Sequence Sequence Analysis, Protein Deep Learning Peptides
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When Protein Structure Embedding Meets Large Language Models.

Genes Dec 23, 2023
Protein structure analysis is essential in various bioinformatics domains such as drug discovery, disease diagnosis, and evolutionary studies. Within structural biology, the classification of protein structures is pivotal, employing machine learning ...
Amino Acid Sequence Language Algorithms Databases, Protein
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DL-PPI: a method on prediction of sequenced protein-protein interaction based on deep learning.

BMC bioinformatics Dec 14, 2023
PURPOSE: Sequenced Protein-Protein Interaction (PPI) prediction represents a pivotal area of study in biology, playing a crucial role in elucidating the mechanistic underpinnings of diseases and facilitating the design of novel therapeutic interventi...
Amino Acid Sequence Protein Interaction Mapping Proteins Deep Learning Neural Networks, Computer
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