AIMC Topic: Sequence Analysis, Protein

Clear Filters Showing 201 to 210 of 262 articles

nhKcr: a new bioinformatics tool for predicting crotonylation sites on human nonhistone proteins based on deep learning.

Briefings in bioinformatics Nov 5, 2021
Lysine crotonylation (Kcr) is a newly discovered type of protein post-translational modification and has been reported to be involved in various pathophysiological processes. High-resolution mass spectrometry is the primary approach for identificatio...
Humans Software Deep Learning Computational Biology Protein Processing, Post-Translational Histones Sequence Analysis, Protein Databases, Protein
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Locating transcription factor binding sites by fully convolutional neural network.

Briefings in bioinformatics Sep 2, 2021
Transcription factors (TFs) play an important role in regulating gene expression, thus identification of the regions bound by them has become a fundamental step for molecular and cellular biology. In recent years, an increasing number of deep learnin...
Sequence Analysis, DNA Response Elements MCF-7 Cells Chromatin Immunoprecipitation Sequencing Amino Acid Motifs Sequence Analysis, Protein A549 Cells Neural Networks, Computer Transcription Factors Humans
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ITP-Pred: an interpretable method for predicting, therapeutic peptides with fused features low-dimension representation.

Briefings in bioinformatics Jul 20, 2021
The peptide therapeutics market is providing new opportunities for the biotechnology and pharmaceutical industries. Therefore, identifying therapeutic peptides and exploring their properties are important. Although several studies have proposed diffe...
Models, Genetic Sequence Analysis, Protein Machine Learning Peptides
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Deep-Kcr: accurate detection of lysine crotonylation sites using deep learning method.

Briefings in bioinformatics Jul 20, 2021
As a newly discovered protein posttranslational modification, histone lysine crotonylation (Kcr) involved in cellular regulation and human diseases. Various proteomics technologies have been developed to detect Kcr sites. However, experimental approa...
Humans Deep Learning Lysine Sequence Analysis, Protein Acylation Protein Processing, Post-Translational Databases, Protein Crotonates
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State-of-the-art web services for de novo protein structure prediction.

Briefings in bioinformatics May 20, 2021
Residue coevolution estimations coupled to machine learning methods are revolutionizing the ability of protein structure prediction approaches to model proteins that lack clear homologous templates in the Protein Data Bank (PDB). This has been patent...
Proteins Humans Sequence Analysis, Protein Animals Databases, Protein Computational Biology Models, Molecular Machine Learning Protein Conformation Software Protein Folding
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AntiCP 2.0: an updated model for predicting anticancer peptides.

Briefings in bioinformatics May 20, 2021
Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides...
Models, Molecular Sequence Analysis, Protein Neoplasms Peptides Machine Learning Humans Databases, Protein Antineoplastic Agents Software Predictive Value of Tests
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Using deep neural networks and biological subwords to detect protein S-sulfenylation sites.

Briefings in bioinformatics May 20, 2021
Protein S-sulfenylation is one kind of crucial post-translational modifications (PTMs) in which the hydroxyl group covalently binds to the thiol of cysteine. Some recent studies have shown that this modification plays an important role in signaling t...
Databases, Protein Sequence Analysis, Protein Sulfenic Acids Neural Networks, Computer Protein Processing, Post-Translational
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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences.

Proceedings of the National Academy of Sciences of the United States of America Apr 13, 2021
In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth ...
Sequence Homology, Amino Acid Sequence Analysis, Protein Amino Acids Protein Conformation Unsupervised Machine Learning
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Learning the molecular grammar of protein condensates from sequence determinants and embeddings.

Proceedings of the National Academy of Sciences of the United States of America Apr 13, 2021
Intracellular phase separation of proteins into biomolecular condensates is increasingly recognized as a process with a key role in cellular compartmentalization and regulation. Different hypotheses about the parameters that determine the tendency of...
Humans Hydrophobic and Hydrophilic Interactions Machine Learning Sequence Analysis, Protein Animals Amino Acid Sequence
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Deep learning for mining protein data.

Briefings in bioinformatics Jan 18, 2021
The recent emergence of deep learning to characterize complex patterns of protein big data reveals its potential to address the classic challenges in the field of protein data mining. Much research has revealed the promise of deep learning as a power...
Data Mining Sequence Analysis, Protein Deep Learning Humans Databases, Protein Animals
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