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  1. Article ; Online: The role of data mining in turning bio-data into Bioinformation.

    Perrizo, William

    Bioinformation

    2007  Volume 1, Issue 9, Page(s) 351–355

    Language English
    Publishing date 2007-01-31
    Publishing country Singapore
    Document type Editorial
    ZDB-ID 2203786-X
    ISSN 0973-2063 ; 0973-2063
    ISSN (online) 0973-2063
    ISSN 0973-2063
    DOI 10.6026/97320630001351
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Book ; Online: Big data analytics in bioinformatics and healthcare

    Li, Ruowang / Perrizo, William / Wang, Baoying

    2015  

    Abstract: This book merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management"--Provided by publisher ... ...

    Institution IGI Global
    Author's details Baoying Wang, Ruowang Li, and William Perrizo, editors
    Abstract "This book merges the fields of biology, technology, and medicine in order to present a comprehensive study on the emerging information processing applications necessary in the field of electronic medical record management"--Provided by publisher

    Advanced datamining using RNAseq data / Yan Guo, Shilin Zhao, Margot Bjoring, Leng Han -- Text mining on big and complex biomedical literature / Boya Xie, Qin Ding, Di Wu -- Interactive data visualization techniques applied to healthcare decision making / Zhecheng Zhu, Heng Bee Hoon, Kiok-Liang Teow -- Large-scale regulatory network analysis from microarray data: application to seed biology / Anamika Basu, Anasua Sarkar -- Detection and employment of biological sequence motifs / Marjan Trutschl, Phillip C. S. R. Kilgore, Rona S. Scott, Christine E. Birdwell, Urska Cvek -- Observer-biased analysis of gene expression profiles / Paulo Fazendeiro, José Valente de Oliveira -- Heuristic principal component analysis-based unsupervised feature extraction and its application to bioinformatics / Y-H. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, Yoshiki Murakami, Akira Okamoto -- The role of big data in radiation oncology: challenges and potentials / Issam El Naqa -- Analysis of genomic data in a cloud computing environment / Philip Groth, Gerhard Reuter, Sebastian Thieme -- Pathway analysis and its applications / Ravi Mathur, Alison Motsinger-Reif -- Computational systems biology perspective on tuberculosis in big data era: challenges and future goals / Amandeep Kaur Kahlon, Ashok Sharma -- Bioinformatics-driven big data analytics in microbial research / Ratna Prabha, Anil Rai, D. P. Singh -- Perspectives on data integration in human complex disease analysis / Kristel Van Steen, Nuria Malats -- Current study designs, methods, and future directions of genetic association mapping / Jami Jackson, Alison Motsinger-Reif -- Personalized disease phenotypes from massive OMICs data / Hans Binder, Lydia Hopp, Kathrin Lembcke, Henry Wirth -- Intellectual property protection for synthetic biology, including bioinformatics and computational intelligence / Matthew K. Knabel, Katherine Doering, Dennis S. Fernandez -- Clinical data linkages in spinal cord injuries (SCI) in Australia: what are the concerns? / Jane Moon, Mary P. Galea, Megan Bohensky -- The benefits of big data analytics in the healthcare sector: what are they and who benefits? / Andrea Darrel, Margee Hume, Timothy Hardie, Jeffery Soar
    MeSH term(s) Biomedical Research/methods ; Computational Biology/methods ; Data Mining/methods ; Electronic Health Records
    Keywords Computational biology ; Data mining ; Medical records/Data processing ; Medizin ; Datenanalyse ; Gesundheitswesen ; Bioinformatik ; Massendaten
    Language English
    Size 1 Online-Ressource (PDFs (528 pages))
    Publisher IGI Global
    Publishing place Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pa., 17033, USA)
    Document type Book ; Online
    Note Includes bibliographical references ; Restricted to subscribers or individual electronic text purchasers
    ISBN 1466666110 ; 9781466666115 ; 9781466666122 ; 9781466666146 ; 1466666129 ; 1466666145
    Database ECONomics Information System

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  3. Article: CARIBIAM: constrained Association Rules using Interactive Biological IncrementAl Mining.

    Rahal, Imad / Rahhal, Riad / Wang, Baoying / Perrizo, William

    International journal of bioinformatics research and applications

    2008  Volume 4, Issue 1, Page(s) 28–48

    Abstract: This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the ... ...

    Abstract This paper analyses annotated genome data by applying a very central data-mining technique known as Association Rule Mining (ARM) with the aim of discovering rules and hypotheses capable of yielding deeper insights into this type of data. In the literature, ARM has been noted for producing an overwhelming number of rules. This work proposes a new technique capable of using domain knowledge in the form of queries in order to efficiently mine only the subset of the associations that are of interest to investigators in an incremental and interactive manner.
    MeSH term(s) Algorithms ; Base Sequence ; Chromosome Mapping/methods ; Database Management Systems ; Databases, Genetic ; Information Storage and Retrieval/methods ; Molecular Sequence Data ; Sequence Analysis, DNA/methods ; Software ; User-Computer Interface
    Language English
    Publishing date 2008-02-20
    Publishing country Switzerland
    Document type Journal Article
    ISSN 1744-5485
    ISSN 1744-5485
    DOI 10.1504/IJBRA.2008.017162
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Book ; Conference proceedings: Computer applications in industry and engineering

    Perrizo, William

    proceedings of the ISCA 11th international conference, Las Vegas, Nevada, U.S.A., November 11 - 13, 1998

    1998  

    Institution International Conference on Computer Applications in Industry and Engineering
    International Society for Computers and Their Applications
    Event/congress ISCA International Conference on Computer Applications in Industry and Engineering (11, 1998.11.11-13, LasVegasNev.)
    Author's details ed.: W. Perrizo
    Language English
    Size VII, 316 S, Ill., graph. Darst, 28 cm
    Publisher ISCA, International Society for Computers and their Applications
    Publishing place Cary, NC
    Document type Book ; Conference proceedings
    Note Includes bibliographical references
    ISBN 1880843269 ; 9781880843260
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  5. Article ; Online: PARM--an efficient algorithm to mine association rules from spatial data.

    Ding, Qin / Ding, Qiang / Perrizo, William

    IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society

    2008  Volume 38, Issue 6, Page(s) 1513–1524

    Abstract: Association rule mining, originally proposed for market basket data, has potential applications in many areas. Spatial data, such as remote sensed imagery (RSI) data, is one of the promising application areas. Extracting interesting patterns and rules ... ...

    Abstract Association rule mining, originally proposed for market basket data, has potential applications in many areas. Spatial data, such as remote sensed imagery (RSI) data, is one of the promising application areas. Extracting interesting patterns and rules from spatial data sets, composed of images and associated ground data, can be of importance in precision agriculture, resource discovery, and other areas. However, in most cases, the sizes of the spatial data sets are too large to be mined in a reasonable amount of time using existing algorithms. In this paper, we propose an efficient approach to derive association rules from spatial data using Peano Count Tree (P-tree) structure. P-tree structure provides a lossless and compressed representation of spatial data. Based on P-trees, an efficient association rule mining algorithm PARM with fast support calculation and significant pruning techniques is introduced to improve the efficiency of the rule mining process. The P-tree based Association Rule Mining (PARM) algorithm is implemented and compared with FP-growth and Apriori algorithms. Experimental results showed that our algorithm is superior for association rule mining on RSI spatial data.
    MeSH term(s) Algorithms ; Artificial Intelligence ; Association ; Computer Simulation ; Databases, Factual ; Information Storage and Retrieval/methods ; Logistic Models ; Pattern Recognition, Automated/methods ; Statistics as Topic
    Language English
    Publishing date 2008-12
    Publishing country United States
    Document type Journal Article ; Research Support, U.S. Gov't, Non-P.H.S.
    ISSN 1941-0492
    ISSN (online) 1941-0492
    DOI 10.1109/TSMCB.2008.927730
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Support-less association rule mining using Tuple Count Cube

    Ding, Qin / Perrizo, William

    Journal of information & knowledge management : JIKM Vol. 6, No. 4 , p. 271-280

    2007  Volume 6, Issue 4, Page(s) 271–280

    Author's details Qin Ding and William Perrizo
    Keywords Wissensmanagement ; Data Mining ; Datenmodell
    Language English
    Size graph. Darst.
    Publisher IKMS
    Publishing place Singapore
    Document type Article
    ZDB-ID 2225563-1
    Database ECONomics Information System

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  7. Article: Comprehensive vertical sample-based KNN/LSVM classification for gene expression analysis.

    Pan, Fei / Wang, Baoying / Hu, Xin / Perrizo, William

    Journal of biomedical informatics

    2004  Volume 37, Issue 4, Page(s) 240–248

    Abstract: Classification analysis of microarray gene expression data has been widely used to uncover biological features and to distinguish closely related cell types that often appear in the diagnosis of cancer. However, the number of dimensions of gene ... ...

    Abstract Classification analysis of microarray gene expression data has been widely used to uncover biological features and to distinguish closely related cell types that often appear in the diagnosis of cancer. However, the number of dimensions of gene expression data is often very high, e.g., in the hundreds or thousands. Accurate and efficient classification of such high-dimensional data remains a contemporary challenge. In this paper, we propose a comprehensive vertical sample-based KNN/LSVM classification approach with weights optimized by genetic algorithms for high-dimensional data. Experiments on common gene expression datasets demonstrated that our approach can achieve high accuracy and efficiency at the same time. The improvement of speed is mainly related to the vertical data representation, P-tree,Patents are pending on the P-tree technology. This work is partially supported by GSA Grant ACT#:K96130308. and its optimized logical algebra. The high accuracy is due to the combination of a KNN majority voting approach and a local support vector machine approach that makes optimal decisions at the local level. As a result, our approach could be a powerful tool for high-dimensional gene expression data analysis.
    MeSH term(s) Algorithms ; Artificial Intelligence ; Diagnosis, Computer-Assisted/methods ; Gene Expression Profiling/methods ; Genetic Testing/methods ; Humans ; Models, Biological ; Models, Statistical ; Neoplasms/diagnosis ; Neoplasms/genetics ; Oligonucleotide Array Sequence Analysis/methods ; Pattern Recognition, Automated/methods ; Signal Processing, Computer-Assisted
    Language English
    Publishing date 2004-08
    Publishing country United States
    Document type Comparative Study ; Evaluation Studies ; Journal Article ; Research Support, Non-U.S. Gov't ; Validation Studies
    ZDB-ID 2057141-0
    ISSN 1532-0480 ; 1532-0464
    ISSN (online) 1532-0480
    ISSN 1532-0464
    DOI 10.1016/j.jbi.2004.07.003
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Book ; Conference proceedings ; Online: The Structure of Attractors in Dynamical Systems

    Markley, Nelson / Martin, John / Perrizo, William

    Proceedings, North Dakota State University, June 20–24, 1977

    (Lecture Notes in Mathematics ; 668)

    1978  

    Series title Lecture Notes in Mathematics ; 668
    Language English
    Size Online-Ressource
    Publisher Springer
    Publishing place Berlin u.a.
    Document type Book ; Conference proceedings ; Online
    ISBN 9783540089254 ; 354008925X
    DOI 10.1007/BFb0101774
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  9. Book ; Online ; Conference proceedings: The Structure of Attractors in Dynamical Systems

    Markley, Nelson / Martin, John / Perrizo, William

    Proceedings, North Dakota State University, June 20–24, 1977

    (Lecture Notes in Mathematics ; 668)

    1978  

    Series title Lecture Notes in Mathematics ; 668
    Keywords Mathematics, general ; Mathematics
    Language English
    Size Online-Ressource
    Publisher Springer
    Publishing place Berlin u.a.
    Document type Book ; Online ; Conference proceedings
    ISBN 9783540089254 ; 354008925X
    DOI 10.1007/BFb0101774
    Database Special collection on veterinary medicine and general parasitology

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