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.
Recommender systems are increasingly exposed to anomalous user behavior that can distort recommendation outcomes and compromise system reliability. In real-world settings, explicit labels identifying malicious activity are rarely available, motivating the adoption of unsupervised…
Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding fake news in Urdu is difficult because t…
Drug–drug interaction (DDI) prediction plays a critical role in optimizing therapeutic outcomes and enhancing patient safety. DDIs pose challenges in drug discovery, often leading to adverse effects, reduced efficacy, or unexpected outcomes. AI in DDIs acts as an effective tool f…
Political violence poses a significant challenge to global stability, underscoring the need for comparative analytical models that support analytical interpretation of structured conflict data. This paper presents a comparative evaluation of 12 machine learning approaches, includ…
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…
Churn prediction has become one of the core concepts in customer relationship management within the insurances, telecom, and internet service provider industries, which is essential in customer retention. Therefore, this study attempts to analyze the effectiveness of the advanced…