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Network pharmacology which is based on bioinformatics and system biology knowledge has been employed into the field of Traditional Chinese Medicine (TCM) researches in recent years. In order to summarize current available bioinformatics databases, especially those can be used for TCM formulae study; a systematic search of Chinese literature by May 2017 was conducted. Results showed that research methods...
This study attempts to develop and design an occupational exposure declaration and monitoring system software for medical staff with multiple functions and convenient for users, which will be the beneficial supplement of Hospital Information system (HIS). Through investigation and documents research, we try to comprehend the procedure of occupational exposure declaration and monitoring, determine...
Acute lymphoblastic leukemia (ALL) is the most prevalent neoplasia among children, and drug resistance is still a major cause of chemotherapy failure in pediatric ALL. Prior research has shown that microRNAs (miRNAs) can play roles in such phenomenon, but detailed regulation mechanisms are far from completely understood. We utilized a semantic analysis approach and its MeSH term filtering mechanisms...
Most state-of-the-art graph kernels only take local graph properties into account, i.e., the kernel is computed with regard to properties of the neighborhood of vertices or other small substructures. On the other hand, kernels that do take global graph properties into account may not scale well to large graph databases. Here we propose to start exploring the spacebetween local and global graph kernels,...
Hospital information system is considered as one of the most important branches of the Medical Informatics by the International Academia Community, with the essence of integrating all the hospital departments into a large information network to facilitate the whole hospital system. Given the issue of “difficult to be hospitalized” in China, a set of safe, stable and easy-to-handle beds resource management...
We propose a novel, semantic-reasoning-based approach to look for potentially adverse drug-drug interactions (DDIs) by using a knowledge-base of biomedical public ontologies and datasets in a semantic graph representation. This approach makes it possible to find previously unknown relations between different biological entities like drugs, proteins and biological processes, and perform inferences...
The purpose of this research is to explore and identify the vulnerabilities in OpenEMR 5.0.0, which is a free and open source medical practice management application. We are to provide recommendations/suggestions to OpenEMR developers on identifying the vulnerabilities. We chose to use vulnerabilities scanning tools to manually explore the demo site of OpenEMR 5.0.0. The targeted vulnerabilities belong...
Nowadays, vehicles have become a very significant role in transport system which a significant issue in various cities around the world, especially in developing countries resulting in turn traffic congestion, massive delays, increased fuel wastage. There are many alternative systems, such as parking places, building bridges. However at the present time, Intelligent Transport System is becoming more...
Article is dedicated to problem of creating the geometric database of products, that required for integration CAD and PDM technologies applicable in product lifecycle management process. As example are considered agricultural machinery tools' geometric data. Cite the forms of geometric data those applying in this process and structural analysis of the cluster system's connections of the components...
Modern drug discovery organizations generate large volumes of SAR data. A promising methodology that can be used to mine this chemical data to identify novel structure-activity relationships is the matched molecular pair (MMP) methodology. However, before the full potential of the MMP methodology can be utilized, a MMP identification method that is capable of identifying all MMPs in large chemical...
Most of the available robot programming by demonstration (PbD) approaches focus on learning a single task, in a given environmental situation. In this paper, we propose to learn multiple tasks together, within a common environment, using one of the available PbD approaches. Task-parameterized Gaussian mixture model (TP-GMM) is used at the core of the proposed approach. A database of TP-GMMs will be...
Technology in devices such as SmartPhones is transforming people's lives. It's also being incorporated into homes in various ways, and hence Smart Environments are becoming more accessible and real. This work focuses on studying and testing a Bayesian Network for anticipating inhabitant interactions with a Smart Environment. It also uses Multi-Agent Systems to model the environment's functionalities...
Gender is one of the most useful facial attributes which are detected from human face images. In this work, we introduce a new gender classification system based on features extracted by Local Phase Quantization (LPQ) operators from intensity and Monogenic images. More detailed, the LPQ features are obtained from the input image (the intensity one) and from three other Monogenic components in the...
The number of software vulnerabilities discovered and publicly disclosed is increasing every year; however, only a small fraction of them is exploited in real-world attacks. With limitations on time and skilled resources, organizations often look at ways to identify threatened vulnerabilities for patch prioritization. In this paper, we present an exploit prediction model that predicts whether a vulnerability...
The increased popularity of Massive Open Online Courses (MOOC) and e-learning has constantly increased video-based online education platforms. There are also many video lectures for software engineering education in online education platforms. Although online lectures have many advantages, there are also limitations. We performed a verification research to see if high frequency words can detect mind...
Distance or similarity measures are essence components used by distance-based recognition techniques. Since the Euclidean distance function is the most widely used distance metric in PCA and LDA recognition systems , no empirical study examines the recognition performance based on these two methods by using different distance functions, especially for biometric authentication domain problems. The...
The rapid increase in available protein structure datasets requires new techniques for fast, yet, effective analysis of protein 3D structures. In this work, we propose a structure-based signature for protein families, suitable for rapid analysis of multidomain domain protein structures. Our method is alignment-free, using protein strings as the basic representation. A key novelty is the two-stage...
Cataract is a cloudiness of eye lens and studies have reported many risk factors for the development of cataract. However, the cumulative effect of multiple factors along with clinical and systemic disease conditions have not been adequately tested due to a limitation in methodology. The collection of a large volume of Electronic Health Records (EHR) offers an opportunity to apply computational tools...
Possible drug side-effects (SEs) are usually verified by many years of repeated clinical trials. Despite the effort, some drugs are still expected to cause adverse reactions in some patients. To better predict drug SEs without having to go through the laborious processes of testing and re-testing, machine learning (ML) techniques are more and more used to uncovered patterns in drug data for such purpose...
Many scientific experiments in Bioinformatics are executed as computational workflows. Frequently, it is necessary to re-run an experiment under the original circumstances in which it was run to recognize and validate it. Data provenance concerns the origin of data. Knowing the data source facilitates the understanding and analysis of the results, by detailing and documenting the history and the paths...
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