scholarly journals Graphical data mining of cancer mechanisms with SEMA

2019 ◽  
Vol 35 (21) ◽  
pp. 4413-4418 ◽  
Author(s):  
Mustafa Solmaz ◽  
Adam Lane ◽  
Bilal Gonen ◽  
Ogulsheker Akmamedova ◽  
Mehmet H Gunes ◽  
...  
Keyword(s):  
Data Mining ◽  
Web Application ◽  
Cell Cycle Progression ◽  
Cancer Genomics ◽  
Supplementary Information ◽  
Visual Data Mining ◽  
Source Codes ◽  
Molecular Alterations ◽  
Regulation Of Cell Cycle ◽  
The Web

Abstract Motivation An important goal of cancer genomics initiatives is to provide the research community with the resources for the unbiased query of cancer mechanisms. Several excellent web platforms have been developed to enable the visual analyses of molecular alterations in cancers from these datasets. However, there are few tools to allow the researchers to mine these resources for mechanisms of cancer processes and their functional interactions in an intuitive unbiased manner. Results To address this need, we developed SEMA, a web platform for building and testing of models of cancer mechanisms from large multidimensional cancer genomics datasets. Unlike the existing tools for the analyses and query of these resources, SEMA is explicitly designed to enable exploratory and confirmatory analyses of complex cancer mechanisms through a suite of intuitive visual and statistical functionalities. Here, we present a case study of the functional mechanisms of TP53-mediated tumor suppression in various cancers, using SEMA, and identify its role in the regulation of cell cycle progression, DNA repair and signal transduction in different cancers. SEMA is a first-in-its-class web application designed to allow visual data mining and hypothesis testing from the multidimensional cancer datasets. The web application, an extensive tutorial and several video screencasts with case studies are freely available for academic use at https://sema.research.cchmc.org/. Availability and implementation SEMA is freely available at https://sema.research.cchmc.org. The web site also contains a detailed Tutorial (also in Supplementary Information), and a link to the YouTube channel for video screencasts of analyses, including the analyses presented here. The Shiny and JavaScript source codes have been deposited to GitHub: https://github.com/msolmazm/sema. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Data mining in web personalization using the blended deep learning model

2020 ◽  
Vol 20 (3) ◽  
pp. 1507
Author(s):  
Qusay Abdullah Abed ◽  
Osamah Mohammed Fadhil ◽  
Wathiq Laftah Al-Yaseen
Keyword(s):  
Data Mining ◽  
Deep Learning ◽  
Web Application ◽  
Large Data ◽  
Learning Model ◽  
Multidimensional Data ◽  
Data Sets ◽  
Web Personalization ◽  
Deep Learning Model ◽  
The Web

In general, multidimensional data (mobile application for example) contain a large number of unnecessary information. Web app users find it difficult to get the information needed quickly and effectively due to the sheer volume of data (big data produced per second). In this paper, we tend to study the data mining in web personalization using blended deep learning model. So, one of the effective solutions to this problem is web personalization. As well as, explore how this model helps to analyze and estimate the huge amounts of operations. Providing personalized recommendations to improve reliability depends on the web application using useful information in the web application. The results of this research are important for the training and testing of large data sets for a map of deep mixed learning based on the model of back-spread neural network. The HADOOP framework was used to perform a number of experiments in a different environment with a learning rate between -1 and +1. Also, using the number of techniques to evaluate the number of parameters, true positive cases are represent and fall into positive cases in this example to evaluate the proposed model.

scholarly journals VisMade: Visualizing Temporal Information in Databases Structured as Master-Details

2009 ◽  
Vol 6 (2) ◽  
Author(s):  
Edécio Fernando Iepsen ◽  
Paulo Roberto Gomes Luzzardi ◽  
Stanley Loh
Keyword(s):  
Data Mining ◽  
Computer Graphics ◽  
Information Visualization ◽  
Visual Data Mining ◽  
Parallel Coordinates ◽  
Amount Of Information ◽  
New Information ◽  
Present Information ◽  
The Web

Information Visualization is a field of computer graphics which aims to present information graphically, allowing users to better understand a great amount of information. It also allows identifying standards, or even detecting new information which, at first, was not possible to be perceived due to its complex representation. This study briefly describes this field and presents a tool for visual data mining executed on the web, through of the Parallel Coordinates technique, that allow users to analyze information structured in a master/detail format. Other advantage of the tool is its capacity of accepting data from several systems exported by the user in the XML format. A case study is demonstrated in order to exemplify the resources of the tool.

VISUALIZATION-BASED SELECTION-AIMED DATA MINING WITH FUZZY DATA

2006 ◽  
Vol 05 (04) ◽  
pp. 611-621 ◽  
Author(s):  
ALEXANDER V. LOTOV
Keyword(s):  
Data Mining ◽  
Financial Planning ◽  
Web Application ◽  
Relational Databases ◽  
Environmental Planning ◽  
Uncertain Data ◽  
Fuzzy Data ◽  
New Development ◽  
The Web ◽  
Machinery Design

The paper is devoted to a visualization-based method for exploration of relational databases that contain large volumes of uncertain data. The visualization is aimed at exploration of properties of the data and selecting a small number of interesting items from the database. The method introduced here is a new development of the Reasonable Goals method, which has already been implemented on Internet in the form of the Web application server. Thus, the new method can be applied on Internet, too. It can be used for selection-aimed data mining in various fields including environmental planning, machinery design, financial planning (including credit operations), biology and medicine.

scholarly journals GLAD: GLycan Array Dashboard, a visual analytics tool for glycan microarrays

2019 ◽  
Vol 35 (18) ◽  
pp. 3536-3537 ◽  
Author(s):  
Akul Y Mehta ◽  
Richard D Cummings
Keyword(s):  
Data Mining ◽  
Microarray Data ◽  
Visual Analytics ◽  
Supplementary Information ◽  
Glycan Array ◽  
Visual Data Mining ◽  
Array Data ◽  
Glycan Microarray ◽  
Multiple Data ◽  
Data Files

Abstract Motivation Traditional glycan microarray data is typically presented as excel files with limited visualization and interactivity. Thus, comparisons and analysis of glycan array data have been difficult, and there is need for a tool to facilitate data mining of glycan array data. Results GLAD (GLycan Array Dashboard) is a web-based tool to visualize, analyze, present and mine glycan microarray data. GLAD allows users to input multiple data files to create comparisons. GLAD extends the capability of the microarray data to produce more comparative visualizations in the form of grouped bar charts, heatmaps, calendar heatmaps, force graphs and correlation maps in order to analyze broad sets of samples. Additionally, it allows users to filter, sort and normalize the data and view glycan structures in an interactive manner, to facilitate faster visual data mining. Availability and implementation GLAD is freely available for use on the Web at https://glycotoolkit.com/Tools/GLAD/ with all major modern browsers (Edge, Firefox, Chrome, Safari). Supplementary information Full documentation and video tutorials for GLAD can be found on https://glycotoolkit.com/GLAD.

PATHOME-Drug: a subpathway-based polypharmacology drug-repositioning method

2021 ◽  
Author(s):  
Seungyoon Nam ◽  
Sungyoung Lee ◽  
Sungjin Park ◽  
Jinhyuk Lee ◽  
Aron Park ◽  
...  
Keyword(s):  
Web Service ◽  
Drug Targets ◽  
Drug Repositioning ◽  
Disease Status ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Multiple Targets ◽  
Source Codes ◽  
Approved Drugs ◽  
The Web

Abstract Motivation Drug repositioning reveals novel indications for existing drugs and in particular, diseases with no available drugs. Diverse computational drug repositioning methods have been proposed by measuring either drug-treated gene expression signatures or the proximity of drug targets and disease proteins found in prior networks. However, these methods do not explain which signaling subparts allow potential drugs to be selected, and do not consider polypharmacology, i.e. multiple targets of a known drug, in specific subparts. Results Here, to address the limitations, we developed a subpathway-based polypharmacology drug repositioning method, PATHOME-Drug, based on drug-associated transcriptomes. Specifically, this tool locates subparts of signaling cascading related to phenotype changes (e.g. disease status changes), and identifies existing approved drugs such that their multiple targets are enriched in the subparts. We show that our method demonstrated better performance for detecting signaling context and specific drugs/compounds, compared to WebGestalt and clusterProfiler, for both real biological and simulated datasets. We believe that our tool can successfully address the current shortage of targeted therapy agents. Availability and implementation The web-service is available at http://statgen.snu.ac.kr/software/pathome. The source codes and data are available at https://github.com/labnams/pathome-drug. Supplementary information Supplementary data are available at Bioinformatics online.

THE USE OF WEB APPLICATIONS FOR THE SELECTION OF CROP GROWING TECHNOLOGIES

2018 ◽  
Vol 48 (3) ◽  
pp. 84-90 ◽  
Author(s):  
E. A. Lapchenko ◽  
S. P. Isakova ◽  
T. N. Bobrova ◽  
L. A. Kolpakova
Keyword(s):  
Web Application ◽  
Crop Production ◽  
Web Applications ◽  
Weather Forecast ◽  
Technical Institute ◽  
Software Complex ◽  
Agricultural Enterprise ◽  
Weather Situation ◽  
The Web ◽  
Selection Of

It is shown that the application of the Internet technologies is relevant in the selection of crop production technologies and the formation of a rational composition of the machine-and-tractor fl eet taking into account the conditions and production resources of a particular agricultural enterprise. The work gives a short description of the web applications, namely “ExactFarming”, “Agrivi” and “AgCommand” that provide a possibility to select technologies and technical means of soil treatment, and their functions. “ExactFarming” allows to collect and store information about temperature, precipitation and weather forecast in certain areas, keep records of information about crops and make technological maps using expert templates. “Agrivi” allows to store and provide access to weather information in the fi elds with certain crops. It has algorithms to detect and make warnings about risks related to diseases and pests, as well as provides economic calculations of crop profi tability and crop planning. “AgCommand” allows to track the position of machinery and equipment in the fi elds and provides data on the weather situation in order to plan the use of agricultural machinery in the fi elds. The web applications presented hereabove do not show relation between the technologies applied and agro-climatic features of the farm location zone. They do not take into account the phytosanitary conditions in the previous years, or the relief and contour of the fi elds while drawing up technological maps or selecting the machine-and-tractor fl eet. Siberian Physical-Technical Institute of Agrarian Problems of Siberian Federal Scientifi c Center of AgroBioTechnologies of the Russian Academy of Sciences developed a software complex PIKAT for supporting machine agrotechnologies for production of spring wheat grain at an agricultural enterprise, on the basis of which there is a plan to develop a web application that will consider all the main factors limiting the yield of cultivated crops.

Data Visualization Indicator Disease (Malaria, Dengue Fever, and Measles) in The Year 2012-2015

2017 ◽  
Vol 4 (2) ◽  
pp. 87-93
Author(s):  
Immanuel Luigi Da Gusta ◽  
Johan Setiawan
Keyword(s):  
Data Mining ◽  
Human Resources ◽  
Data Visualization ◽  
Health Sector ◽  
Medical Personnel ◽  
Database Systems ◽  
Process Time ◽  
Acceptance Test ◽  
Visual Data Mining ◽  
The Government

The aim of this paper are: to create a data visualization that can assist the Government in evaluating the return on the development of health facilities in the region and province area in term of human resources for medical personnel, to help community knowing the amount of distribution of hospitals with medical personnel in the regional area and to map disease indicator in Indonesia. The issue of tackling health is still a major problem that is not resolved by the Government of Indonesia. There are three big things that become problems in the health sector in Indonesia: infrastructure has not been evenly distributed and less adequate, the lack of human resources professional health workforce, there is still a high number of deaths in the outbreak of infectious diseases. Data for the research are taken from BPS, in total 10,600 records after the Extract, Transform and Loading process. Time needed to convert several publications from PDF, to convert to CSV and then to MS Excel 3 weeks. The method used is Eight-step Data Visualization and Data Mining methodology. Tableau is chosen as a tool to create the data visualization because it can combine each dasboard inside a story interactive, easier for the user to analyze the data. The result is a story with 3 dashboards that can fulfill the requirement from BPS staff and has been tested with a satisfied result in the UAT (User Acceptance Test). Index Terms—Dashboard, data visualization, disease, malaria, Tableau REFERENCES [1] S. Arianto, Understanding of learning and others, 2008. [2] Rainer; Turban, Introduction to Information Systems, Danvers: John Wiley & Sons, Inc, 2007. [3] V. Friedman, Data Visualization Infographics, Monday Inspirition, 2008. [4] D. A. Keim, "Information Visualization and Visual Data Mining," IEEE Transactions on Visualization and Computer Graphics 8.1, pp. 1-8, 2002. [5] Connolly and Begg, Database Systems, Boston: Pearson Education, Inc, 2010. [6] E. Hariyanti, "Pengembangan Metodologi Pembangunan Information Dashboard Untuk Monitoring kinerja Organisasi," Konferensi dan Temu Nasional Teknologi Informasi dan Komunikasi untuk Indonesia, p. 1, 2008. [7] S. Darudiato, "Perancangan Data Warehouse Penjualan Untuk Mendukung Kebutuhan Informasi Eksekutif Cemerlang Skin Care," Seminar Nasional Informatika 2010, pp. E-353, 2010.

Spring Framework for Testing

2020 ◽  
Author(s):  
Darshak Mota ◽  
Neel Zadafiya ◽  
Jinan Fiaidhi
Keyword(s):  
Web Application ◽  
Application Development ◽  
Spring Framework ◽  
Java Application ◽  
Development Framework ◽  
Development Life Cycle ◽  
Form Model ◽  
Project Structure ◽  
Model View ◽  
The Web

Java Spring is an application development framework for enterprise Java. It is an open source platform which is used to develop robust Java application easily. Spring can also be performed using MVC structure. The MVC architecture is based on Model View and Controller techniques, where the project structure or code is divided into three parts or sections which helps to categorize the code files and other files in an organized form. Model, View and Controller code are interrelated and often passes and fetches information from each other without having to put all code in a single file which can make testing the program easy. Testing the application while and after development is an integral part of the Software Development Life Cycle (SDLC). Different techniques have been used to test the web application which is developed using Java Spring MVC architecture. And compares the results among all the three different techniques used to test the web application.

PTTG has a Dual Role of Promotion-Inhibition in the Development of Pituitary Adenomas

2019 ◽  
Vol 26 (11) ◽  
pp. 800-818
Author(s):  
Zujian Xiong ◽  
Xuejun Li ◽  
Qi Yang
Keyword(s):  
Cell Cycle ◽  
Pituitary Adenoma ◽  
Pituitary Adenomas ◽  
Cell Cycle Progression ◽  
Key Factors ◽  
Cycle Progression ◽  
Sister Chromatids ◽  
Regulation Of Cell Cycle ◽  
Late Stages

Pituitary Tumor Transforming Gene (PTTG) of human is known as a checkpoint gene in the middle and late stages of mitosis, and is also a proto-oncogene that promotes cell cycle progression. In the nucleus, PTTG works as securin in controlling the mid-term segregation of sister chromatids. Overexpression of PTTG, entering the nucleus with the help of PBF in pituitary adenomas, participates in the regulation of cell cycle, interferes with DNA repair, induces genetic instability, transactivates FGF-2 and VEGF and promotes angiogenesis and tumor invasion. Simultaneously, overexpression of PTTG induces tumor cell senescence through the DNA damage pathway, making pituitary adenoma possessing the potential self-limiting ability. To elucidate the mechanism of PTTG in the regulation of pituitary adenomas, we focus on both the positive and negative function of PTTG and find out key factors interacted with PTTG in pituitary adenomas. Furthermore, we discuss other possible mechanisms correlate with PTTG in pituitary adenoma initiation and development and the potential value of PTTG in clinical treatment.

Sign in / Sign up

Export Citation Format

Share Document