AIMC Topic: Protein Sorting Signals

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Clinical applicability of deep learning-based respiratory signal prediction models for four-dimensional radiation therapy.

PloS one Oct 18, 2022
For accurate respiration gated radiation therapy, compensation for the beam latency of the beam control system is necessary. Therefore, we evaluate deep learning models for predicting patient respiration signals and investigate their clinical feasibi...
Humans Neoplasms Deep Learning Motion Respiration Protein Sorting Signals
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Deep Learning-Based Remaining Useful Life Estimation of Bearings with Time-Frequency Information.

Sensors (Basel, Switzerland) Sep 29, 2022
In modern industrial production, the prediction ability of remaining useful life of bearings directly affects the safety and stability of the system. Traditional methods require rigorous physical modeling and perform poorly for complex systems. In th...
Neural Networks, Computer Deep Learning Protein Sorting Signals
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Signal Peptides Generated by Attention-Based Neural Networks.

ACS synthetic biology Jul 27, 2020
Short (15-30 residue) chains of amino acids at the amino termini of expressed proteins known as signal peptides (SPs) specify secretion in living cells. We trained an attention-based neural network, the Transformer model, on data from all available o...
Area Under Curve Bacterial Proteins Protein Sorting Signals ROC Curve Machine Learning Bacillus subtilis Databases, Protein
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Signal-3L 3.0: Improving Signal Peptide Prediction through Combining Attention Deep Learning with Window-Based Scoring.

Journal of chemical information and modeling Jul 1, 2020
Signal peptides play an important role in guiding and transferring transmembrane proteins and secreted proteins. In recent years, with the explosive growth of protein sequences, computationally predicting signal peptides and their cleavage sites from...
Neural Networks, Computer Amino Acid Sequence Algorithms Protein Sorting Signals Deep Learning
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The hunt for sORFs: A multidisciplinary strategy.

Experimental cell research Mar 2, 2020
Growing evidence illustrates the shortcomings on the current understanding of the full complexity of the proteome. Previously overlooked small open reading frames (sORFs) and their encoded microproteins have filled important gaps, exerting their func...
Software Animals Computational Biology Humans Neural Networks, Computer Protein Biosynthesis Protein Sorting Signals Open Reading Frames Proteome Plants High-Throughput Nucleotide Sequencing Ribosomes
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SignalP 5.0 improves signal peptide predictions using deep neural networks.

Nature biotechnology Feb 18, 2019
Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish ...
Biotechnology Eukaryota Sequence Analysis, Protein Protein Sorting Signals Archaeal Proteins Computational Biology Bacterial Proteins Amino Acid Sequence Software Algorithms Neural Networks, Computer
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ApoplastP: prediction of effectors and plant proteins in the apoplast using machine learning.

The New phytologist Dec 15, 2017
The plant apoplast is integral to intercellular signalling, transport and plant-pathogen interactions. Plant pathogens deliver effectors both into the apoplast and inside host cells, but no computational method currently exists to discriminate betwee...
Plant Proteins Fungal Proteins Cysteine Conserved Sequence Amino Acid Motifs Machine Learning Proteomics Amino Acid Sequence Protein Sorting Signals Oomycetes
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Identification of New Fungal Peroxisomal Matrix Proteins and Revision of the PTS1 Consensus.

Traffic (Copenhagen, Denmark) Aug 22, 2016
The peroxisomal targeting signal type 1 (PTS1) is a seemingly simple peptide sequence at the C-terminal end of most peroxisomal matrix proteins. PTS1 can be described as a tripeptide with the consensus motif [S/A/C] [K/R/H] L. However, this descripti...
Genome-Wide Association Study Databases, Genetic Saccharomyces cerevisiae Machine Learning Amino Acid Motifs Consensus Sequence Protein Sorting Signals Peroxisome-Targeting Signal 1 Receptor Receptors, Cytoplasmic and Nuclear Genome, Fungal Peroxisomes Saccharomyces cerevisiae Proteins
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DeepSig: deep learning improves signal peptide detection in proteins.

Bioinformatics (Oxford, England) May 15, 2018
MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.
Internet Protein Transport Eukaryota Sequence Analysis, Protein Protein Sorting Signals Software Deep Learning Bacteria
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Exploiting multi-layered vector spaces for signal peptide detection.

International journal of data mining and bioinformatics Jan 1, 2015
Analysing and classifying sequences based on similarities and differences is a mathematical problem of escalating relevance and importance in many scientific disciplines. One of the primary challenges in applying machine learning algorithms to sequen...
Protein Sorting Signals Data Mining Support Vector Machine Molecular Sequence Data Algorithms Databases, Protein Sequence Alignment Pattern Recognition, Automated Peptides Amino Acid Sequence Sequence Analysis, Protein
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