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    BMCBI
    2010
    147views more  BMCBI 2010»
    Learning biological network using mutual information and conditional independence
    13 years 10 months ago
    Learning biological network using mutual information and conditional independence
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    Background: Biological networks offer us a new way to investigate the interactions among different components and address the biological system as a whole. In this paper, a revers...
    Dong-Chul Kim, Xiaoyu Wang, Chin-Rang Yang, Jean G...
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    BMCBI
    2008
    134views more  BMCBI 2008»
    Identification of transcription factor contexts in literature using machine learning approaches
    13 years 10 months ago
    Identification of transcription factor contexts in literature using machine learning approaches
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    Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
    Hui Yang, Goran Nenadic, John A. Keane
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    ICDAR
    2007
    IEEE
    204views Document Analysis» more  ICDAR 2007»
    Energy-Based Models in Document Recognition and Computer Vision
    14 years 4 months ago
    Energy-Based Models in Document Recognition and Computer Vision
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    The Machine Learning and Pattern Recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization pro...
    Yann LeCun, Sumit Chopra, Marc'Aurelio Ranzato, Fu...
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    SAC
    2005
    ACM
    203views Applied Computing» more  SAC 2005»
    Automatic learning of text-to-concept mappings exploiting WordNet-like lexical networks
    14 years 3 months ago
    Automatic learning of text-to-concept mappings exploiting WordNet-like lexical networks
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    A great jump towards the advent of the Semantic Web will take place when a critical mass of web resources is available for use in a semantic way. This goal can be reached by the c...
    Dario Bonino, Fulvio Corno, Federico Pescarmona
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    BMCBI
    2011
    273views Artificial Intelligence» more  BMCBI 2011»
    Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
    13 years 1 months ago
    Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
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    Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
    Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
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