Post-translational modifications (PTMs) of proteins are essential for cellular function. Owing to the high cost and time demands of high-throughput sequencing, machine learning and deep learning methods are being rapidly developed for predicting PTM sites. This manuscript presents a comprehensive review of the current research on the application of intelligent algorithms for predicting PTM sites. It outlines the key steps for identifying modified sites based on intelligent algorithms, including data pre-processing, feature extraction, dimension reduction, and classifier development. This review also discusses potential future research directions in this field, providing valuable insights for advancing the state-of-the-art PTM site prediction. Collectively, this review provides comprehensive knowledge on PTM identification and contributes to the development of advanced predictors in the future.
Style transfer is a technique that learns style features from different domains and applies these features to other images. It can not only play a role in the field of artistic creation but also has important significance in image processing, video processing, and other fields. H…
Skin diseases in melanin-rich skin often present diagnostic challenges due to the unique characteristics of darker skin tones, which can lead to misdiagnosis or delayed treatment. This disparity impacts millions within diverse communities, highlighting the need for accurate, AI-b…
Urban environments increasingly rely on interconnected digital infrastructures like IoT devices, SDN-enabled networks, and cloud platforms to support essential municipal services. Ensuring the resilience of these systems requires advanced, data-driven mechanisms capable of detect…
Tongue diagnosis is a crucial method in traditional Chinese medicine (TCM) for obtaining information about a patient’s health condition. In this study, we propose a tongue image segmentation method based on deep learning and a pixel-level tongue color classification method utiliz…
Artificial intelligence (AI) is becoming increasingly important, especially in the medical field. While AI has been used in medicine for some time, its growth in the last decade is remarkable. Specifically, machine learning (ML) and deep learning (DL) techniques in medicine have…
With the rapid expansion of social media, detecting offensive language has become critically important for healthy online interactions. This poses a considerable challenge for low-resource languages such as Roman Urdu which are widely spoken on platforms like Facebook. In this pa…