Long single-molecular sequencing technologies, such as PacBio circular consensus (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine CpGs (5mCpGs), especially repetitive genomic regions. However, existing methods for 5mCpGs using CCS less accurate robust. Here, we present ccsmeth, a deep-learning method to detect reads. We sequence polymerase-chain-reaction treated M.SssI-methyltransferase of one human sample training ccsmeth. Using long (≥10 Kb) reads, ccsmeth...

AntiCancer Peptides (ACPs) have emerged as promising therapeutic agents for cancer treatment. The time-consuming and costly nature of wet-lab discriminatory methods has spurred the development various machine learning deep learning-based ACP classification methods. Nonetheless, current encountered challenges in efficiently integrating features from peptide modalities, thereby limiting a more comprehensive understanding ACPs further restricting improvement prediction model performance. In...

Abstract Drug side effects have become paramount concerns in drug safety research, ranking as the fourth leading cause of mortality following cardiovascular diseases, cancer, and infectious diseases. Simultaneously, widespread use multiple prescription over-the-counter medications by many patients their daily lives has heightened occurrence resulting from Drug-Drug Interactions (DDIs). Traditionally, assessments relied on resource-intensive time-consuming laboratory experiments. However,...

In recent years, lncRNAs (long non-coding RNAs) have been proved to be closely related many diseases that are seriously harmful human health. Although researches on clarifying the relationships between and developing rapidly, associations still remaining largely unknown. this manuscript, a novel Local Random Walk based prediction model called LRWHLDA is proposed for inferring potential diseases. LRWHLDA, new heterogeneous network established first, which allows can implemented in case of...

Background:We compared the effect of remimazolam and propofol intravenous anesthesia on postoperative delirium in elderly patients undergoing laparoscopic radical resection colon cancer. Material/Methods:One hundred elective operation cancer under general were divided into a group (group R) P) by random number table method.During induction maintenance, R was intravenously injected with to exert sedation; however, P, instead remimazolam.The occurrence assessed Confusion Assessment Method for...

521 Background: Kidney cancer, as a common urological malignancy with poor prognosis, shows significant variations in incidence and mortality rates different countries regions worldwide. This study aims to investigate the global burden trends of kidney cancer from 1990 2021, analyze its associations various factors. Methods: First, data on number cases age-standardized (ASR) incidence, prevalence, mortality, disability-adjusted life years (DALYs) 2021 were collected analyzed globally....

One of the major challenges in drug development is maintaining acceptable levels efficacy and safety throughout various stages clinical trials successfully bringing to market. However, are time-consuming expensive. While there computational methods designed predict likelihood a passing reaching market, these heavily rely on manual feature engineering cannot automatically learn molecular representations, resulting relatively low model performance. In this study, we propose AGPred, an...

Recently, numerous laboratory studies have indicated that many microRNAs (miRNAs) are involved in and associated with human diseases can serve as potential biomarkers drug targets. Therefore, developing effective computational models for the prediction of novel associations between miRNAs could be beneficial achieving an understanding disease mechanisms at miRNA level interactions level. Thus far, only a few miRNA-disease association pairs known, analyzing based on lncRNA limited. In this...

Abstract Long single-molecular sequencing, such as PacBio circular consensus sequencing (CCS) and nanopore is advantageous in detecting DNA 5-methylcytosine (5mC) CpGs, especially repetitive genomic regions. However, existing methods for 5mCpGs using CCS are less accurate robust. Here, we present ccsmeth, a deep-learning method to detect reads. We sequence PCR-treated M.SssI-treated of one human sample training ccsmeth. Using long (≥10Kb) reads, ccsmeth achieves 0.90 accuracy 0.97 AUC on...

The survival of human beings is inseparable from microbes. More and more studies have proved that microbes can affect physiological processes in various aspects are closely related to some diseases. In this paper, based on known microbe-disease associations, a bidirectional weighted network was constructed by integrating the schemes normalized Gaussian interactions recommendations firstly. And then, newly network, computational model called BWNMHMDA developed predict potential relationships...

Drug discovery and drug repurposing often rely on the successful prediction of drug-target interactions (DTIs). Recent advances have shown great promise in applying deep learning to interaction prediction. One challenge building learning-based models is adequately represent drugs proteins that encompass fundamental local chemical environments long-distance information among amino acids (or atoms drugs). Another efficiently model intermolecular between proteins, which plays vital roles DTIs....

Accumulating evidence progressively indicated that microRNAs (miRNAs) play a significant role in the pathogenesis of diseases through many experimental studies; therefore, developing powerful computational models to identify potential human miRNA–disease associations is vital for an understanding disease etiology and pathogenesis. In this paper, weighted interactive network was firstly constructed by combining known associations, as well integrated similarity between miRNAs. Then, new method...

As a frontier field of individualized therapy, microRNA (miRNA) pharmacogenomics facilitates the understanding different individual responses to certain drugs and provides reasonable reference for clinical treatment. However, known drug resistance-associated miRNAs are not yet sufficient support precision medicine. Although existing methods effective, they all focus on modelling miRNA-drug resistance interaction graphs, making their performance bounded by density. In this study, we propose...

Tubby-like proteins (TLPs), which were firstly identified in obese mice, play important roles male gametophyte development, biotic stress response, and abiotic responses plants. To date, the role of TLP genes fruit ripening is largely unknown. Here, through a bioinformatics analysis, we 11 TLPs can be divided into three subgroups tomato (Solanum lycopersicum), model plant for studying development ripening. It was shown that all SlTLPs except SlTLP11 contain both Tub domain F-box domain. An...

A new technique for analgesia called pectoral nerve block is widely used in surgeries of breast cancer. Pectoral type II (Pecs II) has less influence on immunity when compared with general anesthesia method. The purpose this research to demonstrate whether Pecs the recurrence cancer after surgical operation.526 patients were recruited and randomized into group group. Recurrence-free survival (RFS), distant recurrence-free (DRFS), overall (OS) evaluated two groups.Based statistical data, only...

Accurate assessment of the prognosis after colorectal cancer surgery is great significance in patients with cancer. However, there no systematic analysis factors affecting currently.To systematically analyze influence clinical data and serological histological indicators on cancer, to explore that can accurately assess cancer.A total 374 were enrolled. The data, tumor-node-metastasis (TNM) stage, Dukes stage recorded. All received examinations including carcinoembryonic antigen (CEA),...

Accurate breast lesion segmentation in ultrasound images helps radiologists to make exact diagnoses and treatments, which is important increase the survival rate of cancer patients. Recently, deep learning-based methods have demonstrated remarkable results segmentation. However, blurry boundaries noise artifacts still limit performance methods. In this paper, we propose a novel network equipped with focal self-attention block for improving The can incorporate fine-grained local...

Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentrate on sequence context features rarely consider spatial neighborhood features. To address this limitation, we propose a novel residual graph convolutional network structure-based site prediction (RGCNPPIS). Specifically, use GCN module to extract...

Accumulating studies have shown that long non-coding RNAs (lncRNAs) are involved in many biological processes and play important roles a variety of complex human diseases. Developing effective computational models to identify potential relationships between lncRNAs diseases can not only help us understand disease mechanisms at the lncRNA molecular level, but also promote diagnosis, treatment, prognosis, prevention For this paper, network-based model called NBLDA was proposed discover...

DNA methylation plays an important role in a wide range of developmental and physiological processes plants. It is primarily catalyzed regulated by cytosine-5 methyltransferases (C5-MTases) group glycosylases that act as demethylases. To date, no genome-scale analysis the two kiwifruit (Actinidia chinensis) families has been undertaken. In our study, nine C5-MTases seven demethylase genes were identified genome. Through selective evolution analysis, we found there gene duplications...