Johannes Lengler

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The bacteriophage-encoded holin proteins are known to promote bacterial cell lysis by forming lesions within the cytoplasmic membrane. Recently, we have shown that the bacteriophage lambda-holin protein exerts cytotoxic activity also in eukaryotic cells accounting for a reduced tumour growth in vivo. In order to elucidate the mechanisms of(More)
Two optimized forms of green fluorescence proteins (GFP), enhanced GFP (EGFP) and humanized Renilla GFP (hrGFP), were used to track expression of cytochrome P450 2B1 (CYP2B1), an endoplasmic reticulum membrane-bound protein. In transiently expressing HEK293 cells we show that CYP2B1-GFP fusion proteins are stable and functional, whereas the(More)
Sox2 transcription factor is expressed in neural tissues and sensory epithelia from the early stages of development. Particularly, it is known to activate crystallin gene expression and to be involved in differentiation of lens and neural tissues. However, its place in the signaling cascade is not well understood. Here, we report about the response of its(More)
In this article, we formulate for the first time the notion of a quantum evolutionary algorithm. In fact we define a quantum analogue for any elitist (1+1) randomized search heuristic. The quantum evolutionary algorithm, which we call <i>(1+1) quantum evolutionary algorithm</i> (QEA), is the quantum version of the classical (1+1) evolutionary algorithm(More)
Black-box complexity is a complexity theoretic measure for how difficult a problem is to be optimized by a general purpose optimization algorithm. It is thus one of the few means trying to understand which problems are tractable for genetic algorithms and other randomized search heuristics. Most previous work on black-box complexity is on artificial test(More)
Black-box complexity theory provides lower bounds for the runtime %classes of black-box optimizers like evolutionary algorithms and serves as an inspiration for the design of new genetic algorithms. Several black-box models covering different classes of algorithms exist, each highlighting a different aspect of the algorithms under considerations. In this(More)
For every engineer it goes without saying: in order to build a reliable system we need components that consistently behave precisely as they should. It is also well known that neurons, the building blocks of brains, do not satisfy this constraint. Even neurons of the same type come with huge variances in their properties and these properties also vary over(More)
In Chung-Lu random graphs, a classic model for real-world networks, each vertex is equipped with a weight drawn from a power-law distribution (for which we fix an exponent 2 < β < 3), and two vertices form an edge independently with probability proportional to the product of their weights. Modern, more realistic variants of this model also equip each vertex(More)