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Integer programming models for computational biology problems

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Abstract

The recent years have seen an impressive increase in the use of Integer Programming models for the solution of optimization problems originating in Molecular Biology. In this survey, some of the most successful Integer Programming approaches are described are described, while a broad overview of application areas being is given in modern Computational Molecular Biology.

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Authors and Affiliations

  1. D.I.M.I, Università di Udine, Viale delle Scienze 206, 3100, Udine, Italy

    Giuseppe Lancia

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  1. Giuseppe Lancia
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Correspondence to Giuseppe Lancia.

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Giuseppe Lancia is an associate professor in operations research at the University of Udine, Italy. He holds the M.S. and the Ph.D. degrees in algorithms, combinatorics and optimization from Carnegie Mellon University, USA. His research interests include combinatorial optimization, mathematical programming, and discrete mathematics, with a special emphasis on their applications to computational molecular biology problems. In this field. Giuseppe Lancia has authored some 30 papers. He has been a member of the program committee of prestigious conferences such as RECOMB and WABI and a co-editor of a special issue of the INFORMS Journal on Computing. Furthermore, he has spent extended periods as a visiting scientist at Sandia National Labs, Albuquerque NM, and Celera Genomics, Rockville MD, working on computational biology problems related to SNPs genotyping, protein structure analysis, sequence alignment, and genome rearrangements.

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Lancia, G. Integer programming models for computational biology problems. J. Comput. Sci. & Technol. 19, 60–77 (2004). https://doi.org/10.1007/BF02944785

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  • DOI: https://doi.org/10.1007/BF02944785

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