CRISPR-Cas is a tool that widely used for gene editing. However, unexpected off-target effects may occur as result of long-term nuclease activity. Anti-CRISPR proteins, which are powerful molecules inhibit the system, have potential to promote better utilization system in editing, especially therapy. Additionally, more in-depth research on these proteins would help researchers understand co-evolution bacteria and phages. Therefore, it necessary collect integrate data various types...

Previously constructed classifiers in predicting eukaryotic essential genes integrated a variety of features including experimental ones. If we can obtain satisfactory prediction using only nucleotide (sequence) information, it would be more promising. Three groups recently identified human cancer cell lines wet experiments and provided wonderful opportunity to accomplish our idea. Here improved the Z curve method into λ-interval form denote composition association information used construct...

Genomic islands are genomic fragments of alien origin in bacterial and archaeal genomes, usually involved symbiosis or pathogenesis. In this work, we described Zisland Explorer, a novel tool to predict based on the segmental cumulative GC profile. Explorer was designed with strategy, as well combination homogeneity heterogeneity sequences. While sequence reflects composition consistence within each island, measures bias between an island core genome. The performance evaluated data sets 11...

Objective To investigate the association between diabetes mellitus (DM) and allergic diseases caused by different allergens explore mechanism of DM in rhinitis (AR) induced ovalbumin (OVA). Methods We established linear regression models to examine correlation specific immunoglobulin E (sIgE) total (TIgE) with glycohemoglobin (A1c) fasting plasma glucose (FPG) individuals retrospectively analyzing 2005-2006 National Health Nutrition Examination Survey database. Participants were classified...

The purpose of this study was to explore whether incorporating the peritumoral region train deep neural networks could improve performance models for predicting prognosis NPC.A total 381 NPC patients who were divided into high- and low-risk groups according progression-free survival retrospectively included. Deeplab v3 U-Net trained build segmentation automatic tumor suspicious lymph nodes. Five datasets constructed by expanding 5, 10, 20, 40, 60 pixels outward from edge automatically...

Essential genes have attracted increasing attention in recent years due to the important functions of these organisms. Among methods used identify essential genes, accurate and efficient computational can make up for deficiencies expensive time-consuming experimental technologies. In this review, we collected researches on gene predictions prokaryotes eukaryotes summarized five predominant types features studies. The include evolutionary conservation, domain information, network topology,...

Pseudo dinucleotide composition (PseDNC) and <italic>Z</italic> curve showed excellent performance in the classification issues of nucleotide sequences bioinformatics.

Investigation of essential genes is significant to comprehend the minimal gene sets cell and discover potential drug targets. In this study, a novel approach based on multiple homology mapping machine learning method was introduced predict genes. We focused 25 bacteria which have characterized The predictions yielded highest area under receiver operating characteristic (ROC) curve (AUC) 0.9716 through tenfold cross-validation test. Proper features were utilized construct models make in...

We aimed to predict the prognosis of advanced nasopharyngeal carcinoma (stage Ⅲ-Ⅳa) using Pre- and Post-treatment MR images based on deep learning (DL).A total 206 patients with primary who were diagnosed treated at Renmin Hospital Wuhan University between June 2012 January 2018 retrospectively selected. A rectangular region interest (ROI), which included tumor area, surrounding tissues organs, was delineated each image. Two Inception-Resnet-V2 transfer models, named Pre-model Post-model,...

Abstract Objectives This study aimed to develop deep learning (DL) models for differentiating between eosinophilic chronic rhinosinusitis (ECRS) and non‐ECRS (NECRS) on preoperative CT. Design Axial spiral CT images were pre‐processed used build the dataset. Two semantic segmentation based U‐net Deeplabv3 trained segment sinus area images. All patient segmented using better‐performing model training testing of transferred efficientnet_b0, resnet50, inception_resnet_v2, Xception neural...

Background The number of biological Knowledge bases/databases storing metabolic pathway information and models has been growing rapidly. These resources are diverse in the type information/data, analytical tools, objectives. Here we present a review most popular databases model repositories, focusing on their scope, content including reactions, enzymes, compounds, genes, applicability. aims to help researchers choose suitable database or repository according data required, by providing an...

Training deep learning (DL) models to automatically recognize diseases in nasopharyngeal MRI is a challenging task, and optimizing the performance of DL difficult.To develop method training anatomical partition-based model which integrates knowledge clinical regions otorhinolaryngology MRI.Single-center retrospective study.A total 2485 patients with (age range 14-82 years, female, 779[31.3%]) 600 people normal nasopharynx 18-78 281[46.8%]) were included.3.0 T; T2WI fast spin-echo...

The relationship between allergies and sinusitis, though extensively studied, remains poorly defined. While several studies proposed a cause-and-effect allergy chronic others reported the lack of any existing association. This study aimed to investigate sinusitis.We conducted cross-sectional using representative sample US population from National Health Nutrition Examination Survey 2005‒2006 (n = 7244). A self-reported questionnaire total allergen-specific IgE levels were used for analysis....

Concurrent chemoradiotherapy (CCRT) and induction chemotherapy (IC) plus CCRT (IC + CCRT) are the main treatments for patients with advanced nasopharyngeal carcinoma (NPC). We aimed to develop deep learning (DL) models using magnetic resonance (MR) imaging predict risk of residual tumor after each 2 provide a reference select best treatment option.A retrospective study was conducted on 424 locoregionally NPC who underwent or IC between June 2012 2019 in Renmin Hospital Wuhan University....

Accurate pre-treatment prediction of distant metastasis in patients with Nasopharyngeal Carcinoma (NPC) enables the implementation appropriate treatment strategies for high-risk individuals.To develop and assess a Convolutional Neural Network (CNN) model using pre-therapy Magnetic Resonance (MR) imaging to predict NPC patients.We retrospectively reviewed data 441 pathologically diagnosed who underwent complete radiotherapy chemotherapy at Renmin Hospital Wuhan University (Hubei, China)...

Adenoid hypertrophy (AH) and allergic rhinitis (AR) are common pediatric diseases, seriously affecting the quality of life growth children. The recurrence rate AH is higher for patients with than those without concurrent AR. Allergen specific immunotherapy (AIT) only effective therapy modifying course diseases. This study sought to investigate efficacy AIT in preventing AR who underwent adenoidectomy.

Objective:To observe the therapeutic effect of local combination（LC） myrtle oil, anthocyanin and hyaluronic acid on allergic rhinitis in rats exposed to PM2.5 explore its mechanism. Method:The were randomly divided into 5 groups: normal group, LC AR AR+PM2.5group AR+PM2.5+LC. After successful establishment model, AR+PM2.5 group AR+PM2.5+ intranasally dripped with suspension, while LC. The symptom score was observed. eosinophil infiltration nasal mucosa observed by hematoxylin-eosin staining....

Abstract Three groups recently identified essential genes in human cancer cell lines using wet experiments, and these are of high values. Herein, we improved the widely used Z curve method by creating a λ-interval curve, which considered interval association information. With this recursive feature elimination technology, computational model was developed to predict gene essentiality. The 5-fold cross-validation test based on our benchmark dataset obtained an area under receiver operating...

Abstract Background : Although it has been reported by several studies that using AI to predict the prognosis of nasopharyngeal carcinoma (NPC) based on magnetic resonance (MR) image, information around tumor was not valued and post-treatment MR images were ignored. Herein we aimed advanced NPC (stage Ⅲ-Ⅳa) pre- deep learning (DL). Methods A total 206 patients with primary who diagnosed treated at Renmin Hospital Wuhan University between June 2012 January 2018 retrospectively selected....

Objective: This study aimed to develop deep learning (DL) models for differentiating between eosinophilic chronic rhinosinusitis (ECRS) and non-eosinophilic (NECRS) on preoperative computed tomography (CT). Methods: A total of 878 (CRS) patients undergoing nasal endoscopic surgery were included. Axial spiral CT images pre-processed used build the dataset. Two semantic segmentation based U-net Deeplabv3 trained segment sinus area in images. All patient segmented using better-performing model...