Abstract. The study of energy landscapes of biopolymers and their models is an important field in bioinformatics [1–6]. For instance the investigation of kinetics or folding simulations are done using methods that are based on sampling or exhaustive enumeration [7–11]. Most of such algorithms are independent of the underlying landscape model. Therefore frameworks for generic algorithms to investigate the landscape properties is needed. Here, we present the Energy Landscape Library (ELL) that allows such a model-independent formulation of generic algorithms dealing with discrete states. The ELL is a completely object-oriented C++ library that is highly modular, easy to extend, and freely available online. It can be used for a fast and easy implementation of new generic algorithms (possibly based on the provided basic method pool) or as a framework to test their properties for different landscape models, which can be formulated straightforward.
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