Data mining and knowledge discovery
A Hybrid Knowledge Discovery Approach for Mining Predictive Biomarkers in Metabolomic Data
... complex and massive biological data issued from metabolomic analytical platforms is a challenge of high ...individuals and a large set of features where predictive biomarkers of clinical out- comes ...
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Discovery of Functional Genes for Systemic Acquired Resistance in Arabidopsis Thaliana through Integrated Data Mining
... integrative data min- ing approach that consists of clustering with various distance measure algorithms, pattern recognition, and motif information in the promoter region of a group of ...in ...
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A hybrid and exploratory approach to knowledge discovery in metabolomic data
... selecting data and patterns, setting thresholds (frequency, confidence), replaying the process at each step whenever ...interaction and iteration –replay– are of main importance within the ...
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Data mining techniques on satellite images for discovery of risk areas
... health data (un- structured and multi-structured data) presents considerable opportunitie s and challenges for the real-time tracking of diseases, predicting disease outbreaks , and ...
15
Improving the knowledge discovery process using ontologies
... in data mining is to extract in- teresting knowledge and information useful for expert ...lift and other ...objective and quantitative ...prior knowledge may significantly ...
8
Algorithms for Data Mining and Bio-informatics
... challenging knowledge discovery from data ...HIV-1 and Human ...drugs and preventing several kinds of ...teins and Human proteins is a particular PPI problem whose study might ...
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Data veracity assessment: enhancing Truth Discovery using a priori knowledge
... Link Mining (LM) consists of a set of techniques that gain insight from graph structure ...sub-graph discovery (Getoor & Diehl, 2005), we are mainly interested in link ...in data, exploiting both ...
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Alzheimer's disease biomarker discovery using in silico literature mining and clinical validation.
... invasive and unsuitable for repeated measures in elderly ...we and others have attempted to mitigate the third of these complications by using a design of biomarker discovery where the in- dependent ...
11
Biodiversity and Environment Data Mining
... species and preserving biological diversity in ecosystems requires to analyze and understand the parameters of this ...considered and linked. This information can be categorized into two types: ...
21
Visualization of data structure, domain knowledge and data mining results: application to breast cancer gene expressions
... Biological Data Visualization, Biological Data Mining, Pattern Recognition, Microarray Data Analysis 1 Introduction There are many computational techniques that may be used within a ...
14
Knowledge Discovery in Hepatitis C Virus Transgenic Mice
... expression data mining that uses a combination of unsupervised and supervised learning techniques to search for useful patterns in the ...validation and elimination of irrelevant data, ...
13
An Approach to Automated Knowledge Discovery in Bioinformatics
... various knowledge discovery technologies and strategies, however, is a challenge to bioinformatics ...analysis and annotation 8,9 , or for microarray data management and analysis ...
10
Visual data mining from visualization to visual information mining
... of data and information, which are mainly caused by the continuous adoption of data warehouses and the extensive use of the Internet and its related technologies, has increased the ...
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Integrating ontological knowledge for iterative causal discovery and vizualisation
... 15] and Maes et al [11] studied which experiments were needed to learn CBN with latent variables under the assumption of faithful distribution ...Graphs and Semi-Markovian Causal Models, in order to perform ...
13
Big Data and Biological Knowledge
... and computable functions), but such that its “computability cannot be proven” within formal number ...theory and use infinitary or geometric tools in the proofs. Tese methods and objects are totally ...
12
Argument Mining: The bottleneck of knowledge and language resources
... relations and their strength between the controversial issue and the argument at ...or data must be triggered to analyze the relation between the potential argument at stake and the ...
9
Mining the Web for Lexical Knowledge to Improve Keyphase Extraction: Learning from Labeled and Unlabeled Data
... 1. Introduction A journal article is often accompanied by a list of keyphrases, composed of about five to fifteen important words and phrases that express the primary topics and themes of the paper. For an ...
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VICKEY: Mining Conditional Keys on Knowledge Bases
... VICKEY and AMIE and finally the number of obtained conditional keys ...rule mining solu- tion cannot handle some of the input datasets in less than 1 ...Museum and Scientist in less than 1 ...
17
Knowledge-based Sequence Mining with ASP
... pattern mining is about identifying frequent sub- sequences in sequence databases [Shen et ...effectiveness and allow for high- throughput extraction from big data ...by data, are now swamped ...
9
Algorithms for data mining
... In this thesis, we study three algorithmic problems in data mining with considera- tion to the analysis of massive data sets. Our work is both theoretical and experimental [r] ...
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