Abstract Motivation With the analysis of characteristic and function circular RNAs (circRNAs), people have realized that they play a critical role in diseases. Exploring relationship between circRNAs diseases is far-reaching significance for searching etiopathogenesis treatment Nevertheless, it inefficient to learn new associations only through biotechnology. Results Consequently, we present computational method, GMNN2CD, which employs graph Markov neural network (GMNN) algorithm predict...

Circular RNAs (circRNAs) are non-coding with a special circular structure produced formed by the reverse splicing mechanism. Increasing evidence shows that can directly bind to RNA-binding proteins (RBP) and play an important role in variety of biological activities. The interactions between circRNAs RBPs key comprehending mechanism posttranscriptional regulation. Accurately identifying binding sites is very useful for analyzing interactions. In past research, some predictors on basis...

Abstract Background Circular RNAs (circRNAs) have been confirmed to play a vital role in the occurrence and development of diseases. Exploring relationship between circRNAs diseases is far-reaching significance for studying etiopathogenesis treating To this end, based on graph Markov neural network algorithm (GMNN) constructed our previous work GMNN2CD, we further considered multisource biological data that affects association circRNA disease developed an updated web server CircDA human...

Abstract Virus-encoded circular RNA (circRNA) participates in the immune response to viral infection, affects human system, and can be used as a target for precision therapy tumor biomarker. The coronaviruses SARS-CoV-1 SARS-CoV-2 (SARS-CoV-1/2) that have emerged recent years are highly contagious high mortality rates. In coronaviruses, little is known about circRNA encoded by SARS-CoV-1/2. Therefore, this study explores whether SARS-CoV-1/2 encodes characteristics functions of circRNA....

Amyloid is an insoluble fibrous protein and its mis-aggregation can lead to some diseases, such as Alzheimer’s disease Creutzfeldt–Jakob’s disease. Therefore, the identification of amyloid essential for discovery understanding We established a novel predictor called RFAmy based on random forest identify amyloid, it employed SVMProt 188-D feature extraction method composition physicochemical properties pse-in-one amino acid composition, autocorrelation pseudo profile-based features predicted...

The major histocompatibility complex (MHC) is a term for all gene groups of antigen. It binds to peptide chains derived from pathogens and displays on the cell surface facilitate T-cell recognition perform series immune functions. MHC molecules are critical in transplantation, autoimmunity, infection, tumor immunotherapy. Combining machine learning algorithms making full use bioinformatics analysis technology, more accurate an important task. paper proposed new method compared with...

Circular RNA (circRNA) plays an important role in the development of diseases, and it provides a novel idea for drug development. Accurate identification circRNAs is deeper understanding their functions. In this study, we developed new classifier, CirRNAPL, which extracts features nucleic acid composition structure circRNA sequence optimizes extreme learning machine based on particle swarm optimization algorithm. We compared CirRNAPL with existing methods, including blast, three datasets...

Drug-drug interactions (DDIs) can result in unexpected pharmacological outcomes, including adverse drug events, which are crucial for discovery. Graph neural networks have substantially advanced our ability to model molecular representations; however, the precise identification of key local structures and capture long-distance structural correlations better DDI prediction interpretation remain significant challenges. Here, we present DrugDAGT, a dual-attention graph transformer framework...

Circular RNAs (circRNAs) have been identified as key players in the progression of several diseases; however, their roles not yet determined because high financial burden biological studies. This highlights urgent need to develop efficient computational models that can predict circRNA-disease associations, offering an alternative approach overcome limitations expensive experimental Although multi-view learning methods widely adopted, most approaches fail fully exploit latent information...

Abstract Background Circular RNAs (circRNAs) can regulate microRNA activity and are related to various diseases, such as cancer. Functional research on circRNAs is the focus of scientific research. Accurate identification important for gaining insight into their functions. Although several circRNA prediction models have been developed, accuracy still unsatisfactory. Therefore, providing a more accurate computational framework predict analyse looping characteristics crucial systematic...

Circular RNAs (circRNAs) are non-coding with a special circular structure produced formed by the reverse splicing mechanism, which play an important role in variety of biological activities. Viruses can encode circRNA, and viral circRNAs have been found multiple single-stranded double-stranded viruses. However, characteristics functions remain unknown. Sequence alignment showed that less conserved than animal, indicating may evolve rapidly. Through analysis sequence it was animals similar...

RNA-binding protein (RBP) is a powerful and wide-ranging regulator that plays an important role in cell development, differentiation, metabolism, health disease. The prediction of RBPs provides valuable guidance for biologists. Although experimental methods have made great progress predicting RBP, they are time-consuming not flexible. Therefore, we developed network model, rBPDL, by combining convolutional neural long short-term memory multilabel classification RBPs. Moreover, to achieve...

Single-guide RNA is a guide (gRNA), which guides the insertion or deletion of uridine residues into kinetoplastid during editing. It small non-coding that can be combined with pre -mRNA pairing. SgRNA critical component CRISPR/Cas9 gene knockout system and play an important role in editing regulation. to accurately quickly identify highly on-target activity sgRNAs. Due its importance, several computational predictors have been proposed predict sgRNAs activity. All these methods clearly...

Inductive logic programming (ILP) is a hot research field in machine learning. Although ILP has obtained great success many domains, most system, deterministic search are used to the hypotheses space, and they easy trap local optima. To overcome shortcomings, an system based on artificial bee colony (ABCILP) proposed this article. ABCILP adopts ABC stochastic examine shortcoming of conquered by search. regard each first-order rule as food source propose some discrete operations generate...

In recent years, intelligent recommendation (IR) technique has been widely utilized in mobile applications (App), which promotes the development of internet and improves user experience. However, to provide service related users' personalized taste, mass privacy information needs be collected by IR Apps. This makes Apps front various security risks, especially risk. It is great significance both theory practice make a risk evaluation on this work, an approach for App based optimized SVM...