@inproceedings{triplet_adbis08,
  author    = {Peter Z. Revesz and
               Thomas Triplet},
  title     = {Reclassification of Linearly Classified Data Using Constraint
               Databases},
  booktitle = {ADBIS},
  year      = {2008},
  pages     = {231-245},
  ee        = {http://dx.doi.org/10.1007/978-3-540-85713-6_17},
  crossref  = {adbis2008}
}
@proceedings{adbis2008,
  editor    = {Paolo Atzeni and
               Albertas Caplinskas and
               Hannu Jaakkola},
  title     = {Advances in Databases and Information Systems, 12th East
               European Conference, ADBIS 2008, Pori, Finland, September
               5-9, 2008. Proceedings},
  booktitle = {ADBIS},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {5207},
  year      = {2008},
  isbn      = {978-3-540-85712-9}
}
@inproceedings{triplet_adbis2009,
  author    = {Peter Z. Revesz and
               Thomas Triplet},
  title     = {Temporal Data Classification Using Linear Classifiers},
  booktitle = {ADBIS},
  year      = {2009},
  pages     = {347-361},
  ee        = {http://dx.doi.org/10.1007/978-3-642-03973-7_25},
  crossref  = {adbis2009}
}
@proceedings{adbis2009,
  editor    = {Janis Grundspenkis and
               Tadeusz Morzy and
               Gottfried Vossen},
  title     = {Advances in Databases and Information Systems, 13th East
               European Conference, ADBIS 2009, Riga, Latvia, September
               7-10, 2009. Proceedings},
  booktitle = {ADBIS},
  publisher = {Springer},
  series    = {Lecture Notes in Computer Science},
  volume    = {5739},
  year      = {2009},
  isbn      = {978-3-642-03972-0},
  ee        = {http://dx.doi.org/10.1007/978-3-642-03973-7}}
@article{triplet_aiim2010,
	author = "Peter Revesz and Thomas Triplet",
	title = "Classification integration and reclassification using constraint databases",
	journal = "Artificial Intelligence in Medicine",
	volume = "49",
	number = "2",
	pages = "79 - 91",
	year = "2010",
	issn = "0933-3657",
	doi = "DOI: 10.1016/j.artmed.2010.02.003",
	url = "http://www.sciencedirect.com/science/article/B6T4K-4YT6N7X-1/2/bd79e2dee5d7b26a64eccf5363232d73"
}@article{Shortridge2011,
title = "Bacterial Protein Structures Reveal Phylum Dependent Divergence",
journal = "Computational Biology and Chemistry",
volume = "35",
number = "1",
pages = "24 - 33",
year = "2011",
issn = "1476-9271",
doi = "DOI: 10.1016/j.compbiolchem.2010.12.004",
url = "http://www.sciencedirect.com/science/article/B73G2-51YYNT6-1/2/e19d8015162e491e84b461641ea86b54",
author = "Matthew D. Shortridge and Thomas Triplet and Peter Revesz and Mark A. Griep and Robert Powers",
keywords = "Proteins",
keywords = "Structure",
keywords = "Sequence",
keywords = "Function",
keywords = "Evolution",
abstract = "
Protein sequence space is vast compared to protein fold space. This raises important questions about how structures adapt to evolutionary changes in protein sequences. A growing trend is to regard protein fold space as a continuum rather than a series of discrete structures. From this perspective, homologous protein structures within the same functional classification should reveal a constant rate of structural drift relative to sequence changes. The clusters of orthologous groups (COG) classification system was used to annotate homologous bacterial protein structures in the Protein Data Bank (PDB). The structures and sequences of proteins within each COG were compared against each other to establish their relatedness. As expected, the analysis demonstrates a sharp structural divergence between the bacterial phyla Firmicutes and Proteobacteria. Additionally, each COG had a distinct sequence/structure relationship, indicating that different evolutionary pressures affect the degree of structural divergence. However, our analysis also shows the relative drift rate between sequence identity and structure divergence remains constant."
}

@inproceedings{triplet_dbkda2011,
  author    = {Thomas Triplet and Gregory Butler},
  title     = {Systems Biology Warehousing: Challenges and Strategies toward Effective Data Integration},
  booktitle = {DBKDA 2011, The Third International Conference on Advances in Databases, Knowledge, and Data Applications},
  publisher = {IARIA},
  year      = {2011},
  pages     = {34 - 40},
}@article{triplet_is2011,
	title = "Temporal data classification using linear classifiers",
	journal = "Information Systems",
	volume = "36",
	number = "1",
	pages = "30 - 41",
	year = "2011",
	note = "Selected Papers from the 13th East-European Conference on Advances in Databases and Information Systems (ADBIS 2009)",
	issn = "0306-4379",
	doi = "DOI: 10.1016/j.is.2010.06.006",
	author = "Peter Revesz and Thomas Triplet",
	keywords = "Classification integration",
	keywords = "Constraint database",
	keywords = "Datalog",
	keywords = "Data integration",
	keywords = "Decision tree",
	keywords = "Reclassification",
	keywords = "SVM",
	abstract = "Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that describes measurements over a period of time in history while the predicted class is expected to occur in the future. We describe a new temporal classification method that improves the accuracy of standard classification methods. The benefits of the method are tested on weather forecasting using the meteorological database from the Texas Commission on Environmental Quality and on influenza using the Google Flu Trends database."
}

@article{triplet_profess2010,
    author = {Triplet, Thomas and Shortridge, Matthew D. and Griep, Mark A. and Stark, Jaime L. and Powers, Robert and Revesz, Peter},
    title = {{PROFESS: a PROtein Function, Evolution, Structure and Sequence database}},
    journal = {Database},
    volume = {2010},
    number = {0},
    pages = {baq011-},
    doi = {10.1093/database/baq011},
    year = {2010}
}
@phdthesis{triplet_dissertation,
	Author = {Thomas Triplet},
	Ee = {http://www.thomastriplet.net/papers/thomastriplet_dissertation.pdf},
	Month = {November},
	School = {University of Nebraska-Lincoln},
	Title = {Classification, Clustering and Data-Mining of Biological Data},
	Year = {2009}
}