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Hidden Neural Networks

Neural Computation (1999) 11 (2): 541–563.
This article has been cited by the following articles in journals that are participating in Crossref Cited-by Linking.
Secondary and Topological Structural Merge Prediction of Alpha-Helical Transmembrane Proteins Using a Hybrid Model Based on Hidden Markov and Long Short-Term Memory Neural Networks
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Hidden neural networks for transmembrane protein topology prediction
  • Ioannis A. Tamposis
  • Dimitra Sarantopoulou
  • Margarita C. Theodoropoulou
  • Evangelia A. Stasi
  • Panagiota I. Kontou
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Computational and Structural Biotechnology Journal (2021) 19: 6090.
JUCHMME: a Java Utility for Class Hidden Markov Models and Extensions for biological sequence analysis
  • Ioannis A Tamposis
  • Konstantinos D Tsirigos
  • Margarita C Theodoropoulou
  • Panagiota I Kontou
  • Georgios N Tsaousis
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  • Zoi I Litou
  • Pantelis G Bagos
  • John Hancock
Bioinformatics (2019) 35 (24): 5309.
Semi-supervised learning of Hidden Markov Models for biological sequence analysis
  • Ioannis A Tamposis
  • Konstantinos D Tsirigos
  • Margarita C Theodoropoulou
  • Panagiota I Kontou
  • Pantelis G Bagos
  • John Hancock
Bioinformatics (2019) 35 (13): 2208.
Diverse classifier ensemble creation based on heuristic dataset modification
  • Hamid Jamalinia
  • Saber Khalouei
  • Vahideh Rezaie
  • Samad Nejatian
  • Karamolah Bagheri-Fard
  • Hamid Parvin
Journal of Applied Statistics (2018) 45 (7): 1209.
Extending hidden Markov models to allow conditioning on previous observations
  • Ioannis A. Tamposis
  • Margarita C. Theodoropoulou
  • Konstantinos D. Tsirigos
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Journal of Bioinformatics and Computational Biology (2018) 16 (05): 1850019.
Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis
  • Ioan Stanculescu
  • Christopher K. I. Williams
  • Yvonne Freer
IEEE Journal of Biomedical and Health Informatics (2014) 18 (5): 1560.
Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes
  • Mathieu N. Galtier
  • Camille Marini
  • Gilles Wainrib
  • Herbert Jaeger
Neural Networks (2014) 56: 10.
Combining Multi-class SVMs with Linear Ensemble Methods that Estimate the Class Posterior Probabilities
  • Yann Guermeur
Communications in Statistics - Theory and Methods (2013) 42 (16): 3011.
An evolutionary method for learning HMM structure: prediction of protein secondary structure
  • Kyoung-Jae Won
  • Thomas Hamelryck
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BMC Bioinformatics (2007) 8 (1)
Evolving the structure of hidden Markov models
  • A. Prugel-Bennett
  • A. Krogh
IEEE Transactions on Evolutionary Computation (2006) 10 (1): 39.
Identifying remote protein homologs by network propagation
  • William S. Noble
  • Rui Kuang
  • Christina Leslie
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The FEBS Journal (2005) 272 (20): 5119.
Prediction of the bonding states of cysteines Using the support vector machines based on multiple feature vectors and cysteine state sequences
  • Yu‐Ching Chen
  • Yeong‐Shin Lin
  • Chih‐Jen Lin
  • Jenn‐Kang Hwang
Proteins: Structure, Function, and Bioinformatics (2004) 55 (4): 1036.
A Hidden Markov Model method, capable of predicting and discriminating β-barrel outer membrane proteins
  • Pantelis G Bagos
  • Theodore D Liakopoulos
  • Ioannis C Spyropoulos
  • Stavros J Hamodrakas
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Prediction of lipoprotein signal peptides in Gram‐negative bacteria
  • Agnieszka S. Juncker
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Protein Science (2003) 12 (8): 1652.
Prediction of the disulfide bonding state of cysteines in proteins with hidden neural networks
  • Pier Luigi Martelli
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  • Rita Casadio
Protein Engineering, Design and Selection (2002) 15 (12): 951.
Prediction of the disulfide‐bonding state of cysteines in proteins at 88% accuracy
  • Pier Luigi Martelli
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Protein Science (2002) 11 (11): 2735.
Applying dynamic context into MLP/HMM speech recognition system
  • Petri Salmela
Computer Speech & Language (2001) 15 (3): 233.

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