Results 41 to 50 of about 3,267,192 (300)
Measuring Data Quality of Geoscience Datasets Using Data Mining Techniques
Data Science Journal, 2007 Currently there are many methods of collecting geoscience data, such as station observations, satellite images, sensor networks, etc. All of these data sources from different regions and time intervals are combined in geoscience research activities today.
Cuo Cai, Kunqing Xie
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Finding novel vulnerabilities of hypomorphic BRCA1 alleles
Molecular Oncology, EarlyView.Synthetic lethality screens performed to identify novel vulnerabilities often model complete gene loss, thereby overlooking patient‐derived hypomorphic mutations. In this study, we have performed genome‐wide CRISPR screens on BRCA1 hypomorphic mutations, showing BRCA1I26A behaves like wild‐type, while BRCA1R1699Q mimics deficiency. Furthermore, we have
Anne Schreuder +10 more
wiley +1 more source
Using Some Data Mining Techniques with Application on Insurance Data [PDF]
المجلة العلمية للدراسات والبحوث المالية والتجاريةFraud considered as the most common problem in insurance companies.Detecting frauds is a difficult problem for insurance companies. This study presents a statistical and data mining techniques.
Dalia Mousa
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Molecular Oncology, EarlyView.BCL9 and BCL9L drive bladder cancer progression by enhancing β‐catenin signaling, promoting proliferation, migration, invasion, and organoid growth. Genetic depletion of BCL9(L) suppresses malignant phenotypes, while pharmacological disruption of the β‐catenin/BCL9(L) complex with ZW4864 inhibits canonical Wnt signaling and tumor‐associated cellular ...
Roland Kotolloshi +11 more
wiley +1 more source
Technometrics, 2001 Methods for knowledge discovery in data bases (KDD) have been studied for more than a decade. New methods are required owing to the size and complexity of data collections in administration, business and science. They include procedures for data query and extraction, for data cleaning, data analysis, and methods of knowledge representation.
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Data Mining Techniques for Text Mining
Indian Journal of Science and Technology, 2016 Semantic text mining is an abstraction of acknowledge based on the meaning. Semantic terms are explained, phrases or words. The searching terms concern their weight is computed corresponding to their synonyms, and the term which has maximum weight is at the top.
Gagandeep Kaur, Hardeep Singh
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Integration of Data Mining Techniques to PostgreSQL Database Manager System
Procedia Computer Science, 2019 Data mining is a technique that allows to obtain patterns or models from the gathered data. This technique is applied in all kind of environments such as in the biological field, educational and financial applications, industry, police, and political ...
A. Viloria +5 more
semanticscholar +1 more source
MagmaFlow: A desktop platform for artificial intelligence‐driven expression analysis
FEBS Open Bio, EarlyView.MagmaFlow is a free, no‐code platform for gene expression analysis. It generates interactive volcano plots, links genes to literature, pathways, and diseases, prioritizes candidates using millions of publications, identifies affected biological processes, builds network diagrams, and exports publication‐ready figures and reports for macOS and Windows ...
Carlos E. Buss +7 more
wiley +1 more source
Data Mining Techniques of XML Data Warehouse [PDF]
Informatică economică, 2007 In this paper we will try to answer to some questions referring to hypertext. In the same time our purpose is to explain what we mean by a query in the context of XQL, and to present a simple model, which will serve as a framework for the future research.
doaj
Data Mining Techniques in Medical Informatics [PDF]
The Open Medical Informatics Journal, 2010 The advent of high-performance computing has benefited various disciplines in finding practical solutions to their problems, and our health care is no exception to this. Signal processing, image processing, and data mining tools have been developed for effective analysis of medical information, in order to help clinicians in making better diagnosis for
Acharya, U. Rajendra, Yu, Wenwei
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