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Science and technology (S&T) linkages have been studied extensively using patent and scientific publication databases. Existing methods used to track S&T linkages, such as analysis of non-patent literature (NPL) or author-inventor matching offer a narrow window for industry level analysis of the data. This paper examines the application of a machine learning algorithm, namely Latent Dirichlet...
Molecular docking is an important method in computational drug discovery. In large-scale virtual screening, millions of small drug-like molecules (chemical compounds) are compared against a designated target protein (receptor). Depending on the utilized docking algorithm for screening, this can take several weeks on conventional HPC systems. However, for certain applications including large-scale...
There is an urgent need to discover or predict DDIs, which would cause serious adverse drug reactions. However, preclinical detection of DDIs bear high cost. Similarity-based computational approaches can be the assistance of experimental approaches. Utilizing pre-market drug similarities, they are able to predict DDIs on a large scale. However, they neglect the topological structure among DDIs and...
Taking care and maintenance of a healthy population is the Strategy of each country. Information and communication technologies in the health care system have led to many changes in order to improve the quality of health care services to patients, rational spending time and reduce costs. In the booming field of IT research, the reach of drug delivery, information on grouping of similar drugs has been...
Identification of counterfeit and substandard drugs, which pose severe risks to patient safety is increasingly important, as inauthentic drugs become more commonplace in developing parts of the world. Though thin layer chromatography (TLC) performed with laboratory-based instruments enables accurate analysis of suspect medicines, there is tremendous interest in development of an inexpensive mobile...
Patients with certain clotting disorders or conditions have a greater risk of developing arterial or venous clots and downstream embolisms, strokes, and arterial insufficiency. These patients need prescription anticoagulant drugs to reduce the possibility of clot formation. However, historically, the clinical decision making workflow in determining the correct type and dosage of anticoagulant(s) is...
Protein-ligand docking programs are valuable tools in the modern drug discovery process for predicting the complex structure of a small molecule ligand and the target protein. Often, the configurational search algorithm in the docking tool consists of global search and local search. The former is to explore widely for promising regions in the search space and the latter is to optimize a candidate...
MS Visual Studio 2010 is used as a development tool and MS SQL Server 2008 database is also selected to design a universal set of Mongolian medicine prescription data-mining system which provides two language versions of Mongolian and Chinese. System can apply code query, the DataGridView controls, DataViews data objects, partially redundant data objects and many other technologies to fast queries...
The maximum common subgraph of two graphs, G1 and G2, is the largest subgraph in G1 that is isomorphic to a subgraph in G2. Finding the maximum common subgraph of two given graphs is known to be a NP-complete problem. An exact solution for the maximum common subgraph problem can be found by an algorithm that transforms the maximum common subgraph problem into a maximal clique enumeration problem....
Fraud detection is interesting research topic and it not only needs data mining techniques but also needs a lot of inputs from domain experts. In health care claims, relationships between physicians and patients form complex communities structures and these communities could lead to potential fraud discoveries. Traditionally, researchers have focused on clustering physicians and patients and tried...
Combinatory drugs are often used in clinical medications for treating some complex diseases such as cancer, diabetes, etc. An extreme challenge in combinatory therapy is that the number of combinations will increase exponentially as the types of drugs increase, which makes it very difficult to choose the optimal concentration. In this paper, we present a new algorithm based on the stationary distribution...
Opinion mining provided less opportunity to discuss their experiences about drugs so reviewing about it was difficult. Recent findings show that online reviews and blogs on drugs are important for patients, marketers and industries. Collecting the information for drugs from the website and analyzing is a challenge. A model is designed by proposing an algorithm which crawls information from the web...
Traditional Chinese medicine (TCM) is a holistic medical approach and the formula's composition discipline is still a mystery. Detecting a formula's structure and herb communities/clusters in TCM Formula networks (TCMF) is a mainly existing problem in data mining of the data sets. In this paper, we devise a novel community similarity calculating method in the process of clustering, which is called...
Delivering medications and fluids intravenously is a common practice in modern medical procedures. Administering medications or fluids directly into a patient's blood circulation results in a predictable and immediate absorption of the drug or fluid administered, this may play a vital role in the treatment of certain acute conditions which require immediate action by drugs or fluids. Syringe Pumps...
Nowadays, the establishment of effective methods of QSAR (Quantitative Structure Activity Relationships) to predict the properties of new chemical compounds and directional computational molecular design of drug compounds are the most important and urgent tasks of bioinformatics. The article proposes a technology based on immune network modeling to determine the substance of new drug compounds. There...
Pharmaceutical industries have declared their need of metrology in the cellular field, to improve new drugs developing time and costs by high-content screening technologies. Cell viability and proliferation tests largely use confluency of cells on a bi-dimensional (2D) surface as a biological measurand. The confluency is measured from images of 2D surface acquired via microscopy techniques. The plethora...
Computer aided drug discovery is a field where recent advances in technology are expected to impact in a significant way the traditional process of drug development. In this paper, an integer differential evolution (IDE) algorithm for De novo drug design is proposed. The aim is to find small molecules that are complementary in shape and charge to a reference molecule by making connections between...
Clustering algorithms play an important role in chemoinformatics and especially in the drug discovery process. Clustering methods may be hierarchical or non-hierarchical. Non-hierarchical algorithms have fast processing for clustering chemical data sets than hierarchical algorithms. One of the most popular non-hierarchical clustering algorithms that are used in many applications in the drug discovery...
Can keyword-hashtag networks, derived from Big Data environments such as Twitter, yield clinicians a powerful tool to extrapolate patterns that may lead to development of new medical therapy and/or drugs? In our paper, we present a systematic network mining method to answer this question. We present HashnetMiner, a new pattern detection algorithm that operates on networks of medical concepts and hashtags...
By attaching RFID tags to products, supply chain participants can identify products and create product data to record the product particulars in transit. Participants along the supply chain share their product data to enable information exchange and support critical decisions in production operations. Such an information sharing essentially requires a data access control mechanism when the product...
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