AIMC Topic: Amino Acid Sequence

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Accurate Prediction of Human Essential Proteins Using Ensemble Deep Learning.

IEEE/ACM transactions on computational biology and bioinformatics Dec 8, 2022
Essential proteins are considered the foundation of life as they are indispensable for the survival of living organisms. Computational methods for essential protein discovery provide a fast way to identify essential proteins. But most of them heavily...
Humans Neural Networks, Computer Amino Acid Sequence Deep Learning Proteins Software
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Long-distance dependency combined multi-hop graph neural networks for protein-protein interactions prediction.

BMC bioinformatics Dec 5, 2022
BACKGROUND: Protein-protein interactions are widespread in biological systems and play an important role in cell biology. Since traditional laboratory-based methods have some drawbacks, such as time-consuming, money-consuming, etc., a large number of...
Amino Acids Amino Acid Sequence Protein Interaction Maps Proteins Neural Networks, Computer
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Ten quick tips for sequence-based prediction of protein properties using machine learning.

PLoS computational biology Dec 1, 2022
The ubiquitous availability of genome sequencing data explains the popularity of machine learning-based methods for the prediction of protein properties from their amino acid sequences. Over the years, while revising our own work, reading submitted m...
Knowledge Chromosome Mapping Amino Acid Sequence Machine Learning
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AlphaPeptDeep: a modular deep learning framework to predict peptide properties for proteomics.

Nature communications Nov 24, 2022
Machine learning and in particular deep learning (DL) are increasingly important in mass spectrometry (MS)-based proteomics. Recent DL models can predict the retention time, ion mobility and fragment intensities of a peptide just from the amino acid ...
Proteomics Amino Acid Sequence Peptides Deep Learning Neural Networks, Computer
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End-to-End Protein Normal Mode Frequency Predictions Using Language and Graph Models and Application to Sonification.

ACS nano Nov 23, 2022
The prediction of mechanical and dynamical properties of proteins is an important frontier, especially given the greater availability of proteins structures. Here we report a series of models that provide end-to-end predictions of nanodynamical prope...
Proteins Learning Amino Acid Sequence Neural Networks, Computer
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Entropy and Variability: A Second Opinion by Deep Learning.

Biomolecules Nov 23, 2022
BACKGROUND: Analysis of the distribution of amino acid types found at equivalent positions in multiple sequence alignments has found applications in human genetics, protein engineering, drug design, protein structure prediction, and many other fields...
Deep Learning Proteins Humans Algorithms Amino Acid Sequence Referral and Consultation Amino Acids
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SENSDeep: An Ensemble Deep Learning Method for Protein-Protein Interaction Sites Prediction.

Interdisciplinary sciences, computational life sciences Nov 8, 2022
PURPOSE: The determination of which amino acid in a protein interacts with other proteins is important in understanding the functional mechanism of that protein. Although there are experimental methods to detect protein-protein interaction sites (PPI...
Deep Learning Proteins Neural Networks, Computer Protein Structure, Secondary Amino Acid Sequence
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Druggable protein prediction using a multi-canal deep convolutional neural network based on autocovariance method.

Computers in biology and medicine Nov 8, 2022
Drug targets must be identified and positioned correctly to research and manufacture new drugs. In this study, rather than using traditional methods for drug expansion, the drug target is determined using machine learning. Machine learning has genera...
Amino Acid Sequence Machine Learning Neural Networks, Computer Amino Acids Drug Delivery Systems
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Collectively encoding protein properties enriches protein language models.

BMC bioinformatics Nov 8, 2022
Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such protein language mod...
Proteins Amino Acid Sequence Natural Language Processing Humans Language
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DeepCPPred: A Deep Learning Framework for the Discrimination of Cell-Penetrating Peptides and Their Uptake Efficiencies.

IEEE/ACM transactions on computational biology and bioinformatics Oct 10, 2022
Cell-penetrating peptides (CPPs) are special peptides capable of carrying a variety of bioactive molecules, such as genetic materials, short interfering RNAs and nanoparticles, into cells. Recently, research on CPP has gained substantial interest fro...
Amino Acid Sequence Deep Learning Machine Learning Cell-Penetrating Peptides Computational Biology
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