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- Johannes Lengler, Harry Holzmüller, Brian Salmons, Walter H Günzburg, Matthias Renner
- Analytical biochemistry
- 2005

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)

- Johannes Lengler, Florian Jug, Angelika Steger
- PloS one
- 2013

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)

- Johannes Lengler, Nicholas Spooner
- FOGA
- 2015

We present a fixed budget analysis of the (1+1) evolutionary algorithm for general linear functions, considering both the quality of the solution after a predetermined 'budget' of fitness function evaluations (a priori) and the improvement in quality when the algorithm is given additional budget, given the quality of the current solution (a posteriori). Two… (More)

- Chukwuma A Agu, Reinhard Klein, +7 authors Christine Hohenadl
- Cellular microbiology
- 2007

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)

- Karl Bringmann, Ralph Keusch, Johannes Lengler
- ArXiv
- 2015

For the theoretical study of real-world networks, we propose a model of scale-free random<lb>graphs with underlying geometry that we call geometric inhomogeneous random graphs (GIRGs).<lb>GIRGs generalize hyperbolic random graphs, which are a popular model to test algorithms for<lb>social and technological networks. Our generalization overcomes some… (More)

- Johannes Lengler, Tobias Bittner, Doris Münster, Alaa El-Din A Gawad, Jochen Graw
- Ophthalmic research
- 2005

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)

- Benjamin Doerr, Johannes Lengler, Timo Kötzing, Carola Doerr
- GECCO
- 2011

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)

- Karl Bringmann, Ralph Keusch, Johannes Lengler
- ArXiv
- 2016

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)

- Carola Doerr, Johannes Lengler
- Algorithmica
- 2015

As in classical runtime analysis the OneMax problem is the most prominent test problem also in black-box complexity theory. It is known that the unrestricted, the memory-restricted, and the ranking-based black-box complexities of this problem are all of order n/log n, where n denotes the length of the bit strings. The combined memory-restricted… (More)

- Daniel Johannsen, Piyush P. Kurur, Johannes Lengler
- GECCO
- 2010

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)