scholarly journals CRISPR-DT: designing gRNAs for the CRISPR-Cpf1 system with improved target efficiency and specificity

2018 ◽  
Author(s):  
Houxiang Zhu ◽  
Chun Liang
Keyword(s):  
Machine Learning ◽  
Web Service ◽  
Genome Editing ◽  
Structural Features ◽  
Learning Technology ◽  
Dna Targeting ◽  
Link Type ◽  
Svm Model ◽  
Service Application

AbstractThe CRISPR-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different gRNA sequences. We reanalyzed the published CRISPR-Cpf1 gRNAs data and found many sequence and structural features related to their target efficiency. Using machine learning technology, a SVM model was created to predict target efficiency for any given gRNAs. We have developed the first web service application, CRISPR-DT (CRISPR DNA Targeting), to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT is available at http://bioinfolab.miamioh.edu/CRISPR-DT.

scholarly journals CRISPR-DT: designing gRNAs for the CRISPR-Cpf1 system with improved target efficiency and specificity

2019 ◽  
Vol 35 (16) ◽  
pp. 2783-2789 ◽  
Author(s):  
Houxiang Zhu ◽  
Chun Liang
Keyword(s):  
Web Service ◽  
Genome Editing ◽  
Support Vector Machine Model ◽  
Structural Features ◽  
Supplementary Information ◽  
Support Vector ◽  
Machine Model ◽  
Guide Rna ◽  
Dna Targeting ◽  
Service Application

Abstract Motivation The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cpf1 system has been successfully applied in genome editing. However, target efficiency of the CRISPR-Cpf1 system varies among different guide RNA (gRNA) sequences. Results In this study, we reanalyzed the published CRISPR-Cpf1 gRNAs data and found many sequence and structural features related to their target efficiency. With the aid of Random Forest in feature selection, a support vector machine model was created to predict target efficiency for any given gRNAs. We have developed the first CRISPR-Cpf1 web service application, CRISPR-DT (CRISPR DNA Targeting), to help users design optimal gRNAs for the CRISPR-Cpf1 system by considering both target efficiency and specificity. CRISPR-DT will empower researchers in genome editing. Availability and implementation CRISPR-DT, mainly implemented in Perl, PHP and JavaScript, is freely available at http://bioinfolab.miamioh.edu/CRISPR-DT. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals CRISPR-RT: A web service for designing CRISPR-C2c2 crRNA with improved target specificity

2017 ◽  
Author(s):  
Houxiang Zhu ◽  
Emily Richmond ◽  
Chun Liang
Keyword(s):  
Web Service ◽  
Genome Editing ◽  
Rna Editing ◽  
Model Organisms ◽  
Future Research ◽  
Target Specificity ◽  
Link Type ◽  
Wide Range ◽  
Set Up

AbstractCRISPR-Cas systems have been successfully applied in genome editing. Recently, the CRISPR-C2c2 system has been reported as a tool for RNA editing. Here we describe CRISPR-RT (CRISPR RNA-Targeting), the first web service to help biologists design the crRNA with improved target specificity for the CRISPR-C2c2 system. CRISPR-RT allows users to set up a wide range of parameters, making it highly flexible for current and future research in CRISPR-based RNA editing. CRISPR-RT covers major model organisms and can be easily extended to cover other species. CRISPR-RT will empower researchers in RNA editing. It is available at http://bioinfolab.miamioh.edu/CRISPR-RT.

Web Service Implementation in Logistics Company uses JSON Web Token and RC4 Cryptography Algorithm

2020 ◽  
Vol 4 (3) ◽  
pp. 591-600
Author(s):  
Mochammad Rizky Royani ◽  
Arief Wibowo
Keyword(s):  
Web Service ◽  
Data Storage ◽  
Growth Potential ◽  
Easy Access ◽  
Access Time ◽  
Mobile Platforms ◽  
Logistics Service ◽  
Authentication Mechanism ◽  
Cryptographic Algorithm ◽  
Service Application

The development of e-commerce in Indonesia in the last five years has significantly increased the growth for logistics service companies. The Indonesian Logistics and Forwarders Association (ALFI) has predicted the growth potential of the logistics business in Indonesia to reach more than 30% by 2020. One of the efforts of logistics business companies to improve services in the logistics services business competition is to implement web service technology on mobile platforms, to easy access to services for customers. This research aims to build a web service with a RESTful approach. The REST architecture has limitations in the form of no authentication mechanism, so users can access and modify data. To improve its services, JSON Web Token (JWT) technology is needed in the authentication process and security of access rights. In terms of data storage and transmission security, a cryptographic algorithm is also needed to encrypt and maintain confidentiality in the database. RC4 algorithm is a cryptographic algorithm that is famous for its speed in the encoding process. RC4 encryption results are processed with the Base64 Algorithm so that encrypted messages can be stored in a database. The combination of the RC4 method with the Base64 method has strengthened aspects of database security. This research resulted in a prototype application that was built with a combination of web service methods, JWT and cryptographic techniques. The test results show that the web service application at the logistics service company that was created can run well with relatively fast access time, which is an average of 176 ms. With this access time, the process of managing data and information becomes more efficient because before making this application the process of handling a transaction takes up to 20 minutes.

Pembangunan Web Service Data Masyarakat Menggunakan REST API dengan Access Token

2018 ◽  
Vol 10 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Muhammad Iqbal Perkasa ◽  
Eko Budi Setiawan
Keyword(s):  
Web Service ◽  
Job Search ◽  
Population Data ◽  
The Public ◽  
Public Data ◽  
Community Data ◽  
The Government ◽  
Rest Api ◽  
Service Application ◽  
Service Data

Data is one of the most important things in this information and information technology era that evolving now. Currently, the government still has not used the public data maximally for administrative purposes. Utilization of this big population data is the creation of a web service application system with REST API where this data will be open and accessible to those who have access. One of the institutions that use this service is the Manpower and Transmigration Service where this system can make the Dinas staff more efficient to create and register job search cards using available community data. This application is able to provide and facilitate many parties, such as data administrators to monitor data usage, registration employee in input data, and people able to register independently. Index Terms—Web service, API, Rest api, People data

EFFICIENCY IMPROVEMENT OF ROAD SURFACE INSPECTION USING MACHINE LEARNING TECHNOLOGY

2017 ◽  
Vol 73 (2) ◽  
pp. I_409-I_415
Author(s):  
Naoko FUKUSHI ◽  
Daishiro KOBAYASHI ◽  
Seiji IWAO ◽  
Ryosuke KASAHARA ◽  
Nobuyoshi YABUKI
Keyword(s):  
Machine Learning ◽  
Road Surface ◽  
Surface Inspection ◽  
Learning Technology ◽  
Efficiency Improvement

scholarly journals 3132 Machine Learning for Prediction of Pathologic Pneumatosis Intestinalis Using CT Scans

2019 ◽  
Vol 3 (s1) ◽  
pp. 60-61
Author(s):  
Kadie Clancy ◽  
Esmaeel Dadashzadeh ◽  
Christof Kaltenmeier ◽  
JB Moses ◽  
Shandong Wu
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Pneumatosis Intestinalis ◽  
Learning Models ◽  
Surgical Decision ◽  
Prediction Task ◽  
Svm Model ◽  
Surgical Decision Making ◽  
Intraoperative Visualization ◽  
Machine Learning Models

OBJECTIVES/SPECIFIC AIMS: This retrospective study aims to create and train machine learning models using a radiomic-based feature extraction method for two classification tasks: benign vs. pathologic PI and operation of benefit vs. operation not needed. The long-term goal of our study is to build a computerized model that incorporates both radiomic features and critical non-imaging clinical factors to improve current surgical decision-making when managing PI patients. METHODS/STUDY POPULATION: Searched radiology reports from 2010-2012 via the UPMC MARS Database for reports containing the term “pneumatosis” (subsequently accounting for negations and age restrictions). Our inclusion criteria included: patient age 18 or older, clinical data available at time of CT diagnosis, and PI visualized on manual review of imaging. Cases with intra-abdominal free air were excluded. Collected CT imaging data and an additional 149 clinical data elements per patient for a total of 75 PI cases. Data collection of an additional 225 patients is ongoing. We trained models for two clinically-relevant prediction tasks. The first (referred to as prediction task 1) classifies between benign and pathologic PI. Benign PI is defined as either lack of intraoperative visualization of transmural intestinal necrosis or successful non-operative management until discharge. Pathologic PI is defined as either intraoperative visualization of transmural PI or withdrawal of care and subsequent death during hospitalization. The distribution of data samples for prediction task 1 is 47 benign cases and 38 pathologic cases. The second (referred to as prediction task 2) classifies between whether the patient benefitted from an operation or not. “Operation of benefit” is defined as patients with PI, be it transmural or simply mucosal, who benefited from an operation. “Operation not needed” is defined as patients who were safely discharged without an operation or patients who had an operation, but nothing was found. The distribution of data samples for prediction task 2 is 37 operation not needed cases and 38 operation of benefit cases. An experienced surgical resident from UPMC manually segmented 3D PI ROIs from the CT scans (5 mm Axial cut) for each case. The most concerning ~10-15 cm segment of bowel for necrosis with a 1 cm margin was selected. A total of 7 slices per patient were segmented for consistency. For both prediction task 1 and prediction task 2, we independently completed the following procedure for testing and training: 1.) Extracted radiomic features from the 3D PI ROIs that resulted in 99 total features. 2.) Used LASSO feature selection to determine the subset of the original 99 features that are most significant for performance of the prediction task. 3.) Used leave-one-out cross-validation for testing and training to account for the small dataset size in our preliminary analysis. Implemented and trained several machine learning models (AdaBoost, SVM, and Naive Bayes). 4.) Evaluated the trained models in terms of AUC and Accuracy and determined the ideal model structure based on these performance metrics. RESULTS/ANTICIPATED RESULTS: Prediction Task 1: The top-performing model for this task was an SVM model trained using 19 features. This model had an AUC of 0.79 and an accuracy of 75%. Prediction Task 2: The top-performing model for this task was an SVM model trained using 28 features. This model had an AUC of 0.74 and an accuracy of 64%. DISCUSSION/SIGNIFICANCE OF IMPACT: To the best of our knowledge, this is the first study to use radiomic-based machine learning models for the prediction of tissue ischemia, specifically intestinal ischemia in the setting of PI. In this preliminary study, which serves as a proof of concept, the performance of our models has demonstrated the potential of machine learning based only on radiomic imaging features to have discriminative power for surgical decision-making problems. While many non-imaging-related clinical factors play a role in the gestalt of clinical decision making when PI presents, we have presented radiomic-based models that may augment this decision-making process, especially for more difficult cases when clinical features indicating acute abdomen are absent. It should be noted that prediction task 2, whether or not a patient presenting with PI would benefit from an operation, has lower performance than prediction task 1 and is also a more challenging task for physicians in real clinical environments. While our results are promising and demonstrate potential, we are currently working to increase our dataset to 300 patients to further train and assess our models. References DuBose, Joseph J., et al. “Pneumatosis Intestinalis Predictive Evaluation Study (PIPES): a multicenter epidemiologic study of the Eastern Association for the Surgery of Trauma.” Journal of Trauma and Acute Care Surgery 75.1 (2013): 15-23. Knechtle, Stuart J., Andrew M. Davidoff, and Reed P. Rice. “Pneumatosis intestinalis. Surgical management and clinical outcome.” Annals of Surgery 212.2 (1990): 160.

scholarly journals Descriptors of Cytochrome Inhibitors and Useful Machine Learning Based Methods for the Design of Safer Drugs

2021 ◽  
Vol 14 (5) ◽  
pp. 472
Author(s):  
Tyler C. Beck ◽  
Kyle R. Beck ◽  
Jordan Morningstar ◽  
Menny M. Benjamin ◽  
Russell A. Norris
Keyword(s):  
United States ◽  
Machine Learning ◽  
Drug Interactions ◽  
The United States ◽  
Structural Features ◽  
Physiochemical Properties ◽  
Drug Dosing ◽  
Therapeutic Outcomes ◽  
Cyp Inhibition ◽  
Cyp Inhibitors

Roughly 2.8% of annual hospitalizations are a result of adverse drug interactions in the United States, representing more than 245,000 hospitalizations. Drug–drug interactions commonly arise from major cytochrome P450 (CYP) inhibition. Various approaches are routinely employed in order to reduce the incidence of adverse interactions, such as altering drug dosing schemes and/or minimizing the number of drugs prescribed; however, often, a reduction in the number of medications cannot be achieved without impacting therapeutic outcomes. Nearly 80% of drugs fail in development due to pharmacokinetic issues, outlining the importance of examining cytochrome interactions during preclinical drug design. In this review, we examined the physiochemical and structural properties of small molecule inhibitors of CYPs 3A4, 2D6, 2C19, 2C9, and 1A2. Although CYP inhibitors tend to have distinct physiochemical properties and structural features, these descriptors alone are insufficient to predict major cytochrome inhibition probability and affinity. Machine learning based in silico approaches may be employed as a more robust and accurate way of predicting CYP inhibition. These various approaches are highlighted in the review.

scholarly journals Automobile tire life prediction based on image processing and machine learning technology

2021 ◽  
Vol 13 (3) ◽  
pp. 168781402110027
Author(s):  
Jianchen Zhu ◽  
Kaixin Han ◽  
Shenlong Wang
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Life Prediction ◽  
Traffic Accidents ◽  
Confusion Matrix ◽  
Small Sample ◽  
Image Feature ◽  
Engineering Practice ◽  
Learning Technology ◽  
K Nearest Neighbor

With economic growth, automobiles have become an irreplaceable means of transportation and travel. Tires are important parts of automobiles, and their wear causes a large number of traffic accidents. Therefore, predicting tire life has become one of the key factors determining vehicle safety. This paper presents a tire life prediction method based on image processing and machine learning. We first build an original image database as the initial sample. Since there are usually only a few sample image libraries in engineering practice, we propose a new image feature extraction and expression method that shows excellent performance for a small sample database. We extract the texture features of the tire image by using the gray-gradient co-occurrence matrix (GGCM) and the Gauss-Markov random field (GMRF), and classify the extracted features by using the K-nearest neighbor (KNN) classifier. We then conduct experiments and predict the wear life of automobile tires. The experimental results are estimated by using the mean average precision (MAP) and confusion matrix as evaluation criteria. Finally, we verify the effectiveness and accuracy of the proposed method for predicting tire life. The obtained results are expected to be used for real-time prediction of tire life, thereby reducing tire-related traffic accidents.

Sign in / Sign up

Export Citation Format

Share Document