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...
Respiration Protein Sorting Signals Humans Deep Learning Motion Neoplasms
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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...
Machine Learning Databases, Protein Area Under Curve Bacterial Proteins ROC Curve Bacillus subtilis Protein Sorting Signals
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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...
Protein Sorting Signals Algorithms Deep Learning Amino Acid Sequence Neural Networks, Computer
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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...
Open Reading Frames Ribosomes Protein Biosynthesis Protein Sorting Signals Animals Computational Biology Humans Plants High-Throughput Nucleotide Sequencing Neural Networks, Computer Proteome Software
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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 ...
Protein Sorting Signals Archaeal Proteins Bacterial Proteins Amino Acid Sequence Eukaryota Sequence Analysis, Protein Biotechnology Algorithms Neural Networks, Computer Software Computational Biology
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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...
Oomycetes Amino Acid Motifs Machine Learning Protein Sorting Signals Fungal Proteins Cysteine Proteomics Amino Acid Sequence Conserved Sequence Plant Proteins
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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...
Receptors, Cytoplasmic and Nuclear Peroxisome-Targeting Signal 1 Receptor Peroxisomes Amino Acid Motifs Genome, Fungal Machine Learning Databases, Genetic Saccharomyces cerevisiae Proteins Protein Sorting Signals Consensus Sequence Genome-Wide Association Study Saccharomyces cerevisiae
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Transfer Learning for Designing Efficient Signal Peptides to Improve the Secretion Level of Recombinant Protein in .

Journal of agricultural and food chemistry Jul 9, 2025
Signal peptides (SPs) play an essential role in determining the secretion efficiency of proteins of interest (POIs). However, the manual identification of SPs with a high secretion potential is both time-consuming and labor-intensive. Recently, many ...
Bacterial Proteins Bacillus amyloliquefaciens Protein Sorting Signals Machine Learning Recombinant 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.
Bacteria Internet Eukaryota Sequence Analysis, Protein Protein Transport Software Protein Sorting Signals Deep Learning
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