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Lysine

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Integration of A Deep Learning Classifier with A Random Forest Approach for Predicting Malonylation Sites.

Genomics, proteomics & bioinformatics
As a newly-identified protein post-translational modification, malonylation is involved in a variety of biological functions. Recognizing malonylation sites in substrates represents an initial but crucial step in elucidating the molecular mechanisms ...

Enhanced d-tagatose production by spore surface-displayed l-arabinose isomerase from isolated Lactobacillus brevis PC16 and biotransformation.

Bioresource technology
In the present study, a new strain of Lactobacillus brevis producing d-tagatose was isolated and identified. Then, the l-arabinose isomerase (L-AI) of this strain was displayed on the spore surface of Bacillus subtilis DB403 by using an anchoring pro...

Prediction of CML contents in the Maillard reaction products for casein-monosaccharides model.

Food chemistry
Response surface methodology (RSM) was applied to predict the processing parameters of the casein-glucose/galactose Maillard reaction (MR) for determining the level of N-(1-carboxymethyl)-l-lysine (CML), one of the typically harmful dietary advanced ...

Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm.

Analytical biochemistry
Lipoylation is a highly conserved post-translational modification which has been found to be involved in many biological processes and closely associated with various metabolic diseases. The accurate identification of lipoylation sites is necessary t...

Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general PseAAC.

Journal of theoretical biology
Lysine acetylation is one of the most important types of protein post-translational modifications (PTM) that are widely involved in cellular regulatory processes. To fully understand the regulatory mechanism of acetylation, identification of acetylat...

A deep learning method to more accurately recall known lysine acetylation sites.

BMC bioinformatics
BACKGROUND: Lysine acetylation in protein is one of the most important post-translational modifications (PTMs). It plays an important role in essential biological processes and is related to various diseases. To obtain a comprehensive understanding o...

DeepUbi: a deep learning framework for prediction of ubiquitination sites in proteins.

BMC bioinformatics
BACKGROUND: Protein ubiquitination occurs when the ubiquitin protein binds to a target protein residue of lysine (K), and it is an important regulator of many cellular functions, such as signal transduction, cell division, and immune reactions, in eu...

Analysis and prediction of human acetylation using a cascade classifier based on support vector machine.

BMC bioinformatics
BACKGROUND: Acetylation on lysine is a widespread post-translational modification which is reversible and plays a crucial role in some biological activities. To better understand the mechanism, it is necessary to identify acetylation sites in protein...

Computational analysis and prediction of lysine malonylation sites by exploiting informative features in an integrative machine-learning framework.

Briefings in bioinformatics
As a newly discovered post-translational modification (PTM), lysine malonylation (Kmal) regulates a myriad of cellular processes from prokaryotes to eukaryotes and has important implications in human diseases. Despite its functional significance, com...

Large-scale comparative assessment of computational predictors for lysine post-translational modification sites.

Briefings in bioinformatics
Lysine post-translational modifications (PTMs) play a crucial role in regulating diverse functions and biological processes of proteins. However, because of the large volumes of sequencing data generated from genome-sequencing projects, systematic id...