AIMC Topic: Acetylation

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AIPred: comprehensive prediction and analysis of non-histone acetylation via protein language model and interpretable machine learning.

BMC biology
BACKGROUND: Non-histone lysine acetylation is a widespread protein post-translational modification that regulates almost all key cellular processes, and its dysregulation is closely associated with various human diseases. Precise identification of no...

Comprehensive characterization of the molecular feature of acetylation in colorectal cancer using integrated single-cell and bulk RNA sequencing.

Scientific reports
Colorectal cancer (CRC) remains a major global health burden with high mortality rates, underscoring the need for effective therapies. This study explores the acetylation characteristics in CRC using single-cell RNA sequencing (scRNA-seq) and weighte...

SSE-Net: A novel network based on sequence spatial equation for Camellia sinensis lysine acetylation identification.

Computational biology and chemistry
Lysine acetylation (Kace) is one of the most important post-translational modifications. It is key to identify Kace sites for understanding regulation mechanisms in Camellia sinensis. In this study, we defined a mathematical formula, named sequence s...

Exploring acetylation-related gene markers in polycystic ovary syndrome: insights into pathogenesis and diagnostic potential using machine learning.

Gynecological endocrinology : the official journal of the International Society of Gynecological Endocrinology
OBJECTIVE: Polycystic ovary syndrome (PCOS) is a prevalent cause of menstrual irregularities and infertility in women, impacting quality of life. Despite advancements, current understanding of PCOS pathogenesis and treatment remains limited. This stu...

Prediction of protein N-terminal acetylation modification sites based on CNN-BiLSTM-attention model.

Computers in biology and medicine
N-terminal acetylation is one of the most common and important post-translational modifications (PTM) of eukaryotic proteins. PTM plays a crucial role in various cellular processes and disease pathogenesis. Thus, the accurate identification of N-term...

Leveraging Protein Dynamics to Identify Functional Phosphorylation Sites using Deep Learning Models.

Journal of chemical information and modeling
Accurate prediction of post-translational modifications (PTMs) is of great significance in understanding cellular processes, by modulating protein structure and dynamics. Nowadays, with the rapid growth of protein data at different "omics" levels, ma...

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...

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...

Rapid LC-MS/MS quantification of cancer related acetylated polyamines in human biofluids.

Talanta
Increased urinary acetylated polyamines (APs) are reported as cancer biomarkers in many studies. N,N-diacetylspermine has been proposed as a biomarker indicative of different cancers in urine and plasma. N-Acetylspermine has previously been found to ...

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...