AIMC Topic: Sequence Analysis, Protein

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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...
Machine Learning Software Humans Proteins Databases, Protein Models, Molecular Animals Computational Biology Sequence Analysis, Protein Protein Conformation 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 Databases, Protein Predictive Value of Tests Peptides Humans Machine Learning Antineoplastic Agents Software Neoplasms
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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 Neural Networks, Computer Sequence Analysis, Protein Protein Processing, Post-Translational Sulfenic Acids
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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 Analysis, Protein Protein Conformation Sequence Homology, Amino Acid Unsupervised Machine Learning Amino Acids
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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...
Machine Learning Animals Amino Acid Sequence Hydrophobic and Hydrophilic Interactions Humans Sequence Analysis, Protein
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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...
Databases, Protein Data Mining Sequence Analysis, Protein Animals Deep Learning Humans
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Variable Length Character N-Gram Embedding of Protein Sequences for Secondary Structure Prediction.

Protein and peptide letters Jan 1, 2021
BACKGROUND: The prediction of a protein's secondary structure from its amino acid sequence is an essential step towards predicting its 3-D structure. The prediction performance improves by incorporating homologous multiple sequence alignment informat...
Protein Structure, Secondary Sequence Analysis, Protein Deep Learning Proteins Databases, Protein
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Improved Prediction of Protein-Protein Interaction Mapping on by Using Amino Acid Sequence Features in a Supervised Learning Framework.

Protein and peptide letters Jan 1, 2021
BACKGROUND: Protein-Protein Interaction (PPI) has emerged as a key role in the control of many biological processes including protein function, disease incidence, and therapy design. However, the identification of PPI by wet lab experiment is a chall...
Computational Biology Support Vector Machine Amino Acid Sequence Protein Interaction Mapping Proteins Humans Protein Interaction Maps Sequence Analysis, Protein
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FastSK: fast sequence analysis with gapped string kernels.

Bioinformatics (Oxford, England) Dec 30, 2020
MOTIVATION: Gapped k-mer kernels with support vector machines (gkm-SVMs) have achieved strong predictive performance on regulatory DNA sequences on modestly sized training sets. However, existing gkm-SVM algorithms suffer from slow kernel computation...
Algorithms Support Vector Machine Proteins Sequence Analysis, Protein Software
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MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization.

Nucleic acids research Jul 2, 2020
MusiteDeep is an online resource providing a deep-learning framework for protein post-translational modification (PTM) site prediction and visualization. The predictor only uses protein sequences as input and no complex features are needed, which res...
Sequence Analysis, Protein Models, Molecular Protein Processing, Post-Translational Internet Protein Conformation Proteins Computer Graphics Software Deep Learning
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