AbstractIn this paper we develop a framework for designing and validating heuristic algorithms for NP-hard problems arising in computational biology and other application areas. We introduce two areas of current research in which we are applying the framework: implicit hitting set problems and analysis of protein–protein interaction networks, with emphasis on a specific problem in each area: multi-genome alignment and colorful connected graph detection
Computational molecular biology has emerged as one of the most exciting interdisciplinary fields, ri...
Biology offers a huge amount and variety of data to be processed. Such data has to be stored, analys...
Theory-oriented approach to the application of contemporary algorithms to bioinformatics. Graph theo...
AbstractIn this paper we develop a framework for designing and validating heuristic algorithms for N...
Modeling biology as classical problems in computer science allows researchers to leverage the wealth...
The interdisciplinary field of systems biology has evolved rapidly over the last few years. Differen...
This chapter deals with some combinatorial optimization problems arising in computational biology. W...
Computational Biology is a fairly new subject that arose in response to the computational problems p...
This paper tackles one of the most known problems in biology: search for an optimal sequences tree t...
Recent advances in sequencing and synthesis technologies have sparked extraordinary growth in large-...
In this thesis we are concerned with constructing algorithms that address problems of biological rel...
The workshop covers research in all aspects of algorithms in bioinformatics. The emphasis is on disc...
This course focuses on the algorithmic and machine learning foundations of computational biology, co...
The consistently growing field of bioinformatics exhibits the success of cooperative work in biology...
The interest of statistical physics for combinatorial optimization is not new, it suffices to think ...
Computational molecular biology has emerged as one of the most exciting interdisciplinary fields, ri...
Biology offers a huge amount and variety of data to be processed. Such data has to be stored, analys...
Theory-oriented approach to the application of contemporary algorithms to bioinformatics. Graph theo...
AbstractIn this paper we develop a framework for designing and validating heuristic algorithms for N...
Modeling biology as classical problems in computer science allows researchers to leverage the wealth...
The interdisciplinary field of systems biology has evolved rapidly over the last few years. Differen...
This chapter deals with some combinatorial optimization problems arising in computational biology. W...
Computational Biology is a fairly new subject that arose in response to the computational problems p...
This paper tackles one of the most known problems in biology: search for an optimal sequences tree t...
Recent advances in sequencing and synthesis technologies have sparked extraordinary growth in large-...
In this thesis we are concerned with constructing algorithms that address problems of biological rel...
The workshop covers research in all aspects of algorithms in bioinformatics. The emphasis is on disc...
This course focuses on the algorithmic and machine learning foundations of computational biology, co...
The consistently growing field of bioinformatics exhibits the success of cooperative work in biology...
The interest of statistical physics for combinatorial optimization is not new, it suffices to think ...
Computational molecular biology has emerged as one of the most exciting interdisciplinary fields, ri...
Biology offers a huge amount and variety of data to be processed. Such data has to be stored, analys...
Theory-oriented approach to the application of contemporary algorithms to bioinformatics. Graph theo...