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    CSB
    2005
    IEEE
    125views Bioinformatics» more  CSB 2005»
    Discriminative Discovery of Transcription Factor Binding Sites from Location Data
    13 years 11 months ago
    Discriminative Discovery of Transcription Factor Binding Sites from Location Data
    Download  conferences.computer.org
    Motivation: The availability of genome-wide location analyses based on chromatin immunoprecipitation (ChIP) data gives a new insight for in silico analysis of transcriptional regu...
    Yuji Kawada, Yasubumi Sakakibara
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    EXACT
    2007
    119views Applied Computing» more  EXACT 2007»
    Learning Models from Temporal-Logic Properties via Explanations
    13 years 7 months ago
    Learning Models from Temporal-Logic Properties via Explanations
    Download  www.aaai.org
    Given a model and a property expressed in temporal logic, a model checker normally produces a counterexample in case the model does not satisfy the property. This counterexample i...
    Miguel A. Carrillo, David A. Rosenblueth
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    KDD
    2008
    ACM
    137views Data Mining» more  KDD 2008»
    Learning classifiers from only positive and unlabeled data
    14 years 5 months ago
    Learning classifiers from only positive and unlabeled data
    Download  cseweb.ucsd.edu
    The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
    Charles Elkan, Keith Noto
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    BMCBI
    2010
    143views more  BMCBI 2010»
    Learning gene regulatory networks from only positive and unlabeled data
    13 years 5 months ago
    Learning gene regulatory networks from only positive and unlabeled data
    Download  www.biomedcentral.com
    Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
    Luigi Cerulo, Charles Elkan, Michele Ceccarelli
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    IJCAI
    2003
    130views Artificial Intelligence» more  IJCAI 2003»
    Learning to Classify Texts Using Positive and Unlabeled Data
    13 years 6 months ago
    Learning to Classify Texts Using Positive and Unlabeled Data
    Download  www.cs.uic.edu
    In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
    Xiaoli Li, Bing Liu
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