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Research Article

ToPS: A Framework to Manipulate Probabilistic Models of Sequence Data

  • André Yoshiaki Kashiwabara,

    Affiliation: Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil

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  • Ígor Bonadio,

    Affiliation: Computer Science Graduate Program, Universidade de São Paulo, São Paulo, Brazil

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  • Vitor Onuchic,

    Affiliation: Bioinformatics Graduate Program, Universidade de São Paulo, São Paulo, Brazil

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  • Felipe Amado,

    Affiliation: Computer Science Undergraduate Program, Universidade de São Paulo, São Paulo, Brazil

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  • Rafael Mathias,

    Affiliation: Computer Science Graduate Program, Universidade de São Paulo, São Paulo, Brazil

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  • Alan Mitchell Durham mail

    aland@usp.br

    Affiliation: Department of Computer Science, Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil

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About the Authors

André Yoshiaki Kashiwabara
Graduate Program in Informatics, Federal University of Technology - Paraná, Cornélio Procópio, Paraná, Brazil
Ígor Bonadio, Rafael Mathias
Computer Science Graduate Program, Universidade de São Paulo, São Paulo, Brazil
Vitor Onuchic
Bioinformatics Graduate Program, Universidade de São Paulo, São Paulo, Brazil
Felipe Amado
Computer Science Undergraduate Program, Universidade de São Paulo, São Paulo, Brazil
Alan Mitchell Durham
Department of Computer Science, Instituto de Matemática e Estatística, Universidade de São Paulo, São Paulo, Brazil

Corresponding Author

Email: aland@usp.br

Competing Interests

The authors have declared that no competing interests exist.

Author Contributions

Conceived and designed the experiments: AYK AMD. Performed the experiments: AYK. Analyzed the data: AYK AMD. Wrote the paper: AYK AMD. Designed and implemented the PairHMM model and related algorithms: VO. Designed and implemented ProfileHMM and related algorithms: FA RM. Implemented the specificaion parser with error reporting and some algorithms of the GHMM probabilistic model: IB.