Research graph
References from iNClassSec-ESM: Discovering potential non-classical secreted proteins through a novel protein language model. Local targets link to admitted publications; unresolved targets remain external evidence.
10.1016/j.jmb.2020.01.015
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Non-classical protein secretion in bacteria
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Non-classical secretion of 1, 4-α-glucan branching enzymes without signal peptides in escherichia coli
10.1016/j.ijbiomac.2019.04.002 · 2019 · External reference
Non-classical secretion of a type i l-asparaginase in bacillus subtilis
10.1016/j.ijbiomac.2021.03.104 · 2021 · External reference
Investigation of non-classical secretion of oxalate decarboxylase in bacillus mojavensis xh1 mediated by exopeptide yydf: mechanism and application
10.1016/j.ijbiomac.2024.130662 · 2024 · External reference
Regulate the hydrophobic motif to enhance the non-classical secretory expression of pullulanase pula in bacillus subtilis
10.1016/j.ijbiomac.2021.10.164 · 2021 · External reference
The n-terminus of 1, 4-α-glucan branching enzyme plays an important role in its non-classical secretion in bacillus subtilis
10.1016/j.fbio.2023.102491 · 2023 · External reference
A novel strategy for protein production using non-classical secretion pathway in bacillus subtilis
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Staphylococcal major autolysin (atl) is involved in excretion of cytoplasmic proteins
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10.1093/protein/gzh037 · External reference
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10.1016/j.peptides.2009.12.026 · External reference
Nclassg+: a classifier for non-classically secreted gram-positive bacterial proteins
10.1186/1471-2105-12-21 · 2011 · External reference
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10.1007/s00253-019-10285-4 · External reference
10.1007/s00284-015-0915-6
10.1007/s00284-015-0915-6 · External reference
PeNGaRoo, a combined gradient boosting and ensemble learning framework for predicting non-classical secreted proteins
10.1093/bioinformatics/btz629 · 2019 · External reference
Nonclasgp-pred: robust and efficient prediction of non-classically secreted proteins by integrating subset-specific optimal models of imbalanced data
2020 · External reference
ASPIRER: a new computational approach for identifying non-classical secreted proteins based on deep learning
10.1093/bib/bbac031 · 2022 · External reference
insp-gcaap: identifying nonclassical secreted proteins using global composition of amino acid properties
10.1002/pmic.202100134 · 2023 · External reference
Classification of nuclear receptors based on amino acid composition and dipeptide composition
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Unresolved reference
External reference
10.1093/nar/gky1049
10.1093/nar/gky1049 · External reference
10.1038/s41592-019-0598-1
10.1038/s41592-019-0598-1 · External reference
Unresolved reference
2019 · External reference
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences
10.1073/pnas.2016239118 · 2021 · External reference
Prottrans: toward understanding the language of life through self-supervised learning
10.1109/tpami.2021.3095381 · 2021 · External reference
Language models of protein sequences at the scale of evolution enable accurate structure prediction
2022 · External reference
Contrastive learning in protein language space predicts interactions between drugs and protein targets
10.1073/pnas.2220778120 · 2023 · External reference
Embeddings from protein language models predict conservation and variant effects
10.1007/s00439-021-02411-y · 2022 · External reference
Leveraging molecular structure and bioactivity with chemical language models for de novo drug design
10.1038/s41467-022-35692-6 · 2023 · External reference
Controllable protein design with language models
10.1038/s42256-022-00499-z · 2022 · External reference
Protein language models uncover carbohydrate-active enzyme function in metagenomics
2023 · External reference
Simulating 500 million years of evolution with a language model
2024 · External reference
10.1007/s00284-015-0915-6
10.1007/s00284-015-0915-6 · External reference
10.1093/bioinformatics/btq003
10.1093/bioinformatics/btq003 · External reference
ifeature: a python package and web server for features extraction and selection from protein and peptide sequences
10.1093/bioinformatics/bty140 · 2018 · External reference
Possum: a bioinformatics toolkit for generating numerical sequence feature descriptors based on pssm profiles
10.1093/bioinformatics/btx302 · 2017 · External reference
10.1093/nar/gkt1223
10.1093/nar/gkt1223 · External reference
Mgnify: the microbiome analysis resource in 2020
2020 · External reference
10.1093/nar/gkac976
10.1093/nar/gkac976 · External reference
10.1002/pro.4205
10.1002/pro.4205 · External reference
10.1093/nar/gky1004
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10.1093/nar/gkad1011
10.1093/nar/gkad1011 · External reference
10.1126/science.ade2574
10.1126/science.ade2574 · External reference
10.1007/978-3-540-39964-3_62
10.1007/978-3-540-39964-3_62 · 2003 · External reference
10.1023/a:1010933404324
10.1023/a:1010933404324 · External reference
Support vector machines
10.1109/5254.708428 · 1998 · External reference
10.1145/2939672.2939785
10.1145/2939672.2939785 · 2016 · External reference
Unresolved reference
2017 · External reference
Unresolved reference
2018 · External reference
10.1613/jair.953
10.1613/jair.953 · External reference
Unresolved reference
2020 · External reference
Unresolved reference
2017 · External reference
10.1145/1015330.1015435
10.1145/1015330.1015435 · 2004 · External reference
Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy
10.1109/tpami.2005.159 · 2005 · External reference
Unresolved reference
1995 · External reference
Prediction of blood–brain barrier penetrating peptides based on data augmentation with augur
10.1186/s12915-024-01883-4 · 2024 · External reference
