@article{1604,
  abstract     = {We consider the quantitative analysis problem for interprocedural control-flow graphs (ICFGs). The input consists of an ICFG, a positive weight function that assigns every transition a positive integer-valued number, and a labelling of the transitions (events) as good, bad, and neutral events. The weight function assigns to each transition a numerical value that represents ameasure of how good or bad an event is. The quantitative analysis problem asks whether there is a run of the ICFG where the ratio of the sum of the numerical weights of good events versus the sum of weights of bad events in the long-run is at least a given threshold (or equivalently, to compute the maximal ratio among all valid paths in the ICFG). The quantitative analysis problem for ICFGs can be solved in polynomial time, and we present an efficient and practical algorithm for the problem. We show that several problems relevant for static program analysis, such as estimating the worst-case execution time of a program or the average energy consumption of a mobile application, can be modeled in our framework. We have implemented our algorithm as a tool in the Java Soot framework. We demonstrate the effectiveness of our approach with two case studies. First, we show that our framework provides a sound approach (no false positives) for the analysis of inefficiently-used containers. Second, we show that our approach can also be used for static profiling of programs which reasons about methods that are frequently invoked. Our experimental results show that our tool scales to relatively large benchmarks, and discovers relevant and useful information that can be used to optimize performance of the programs.},
  author       = {Chatterjee, Krishnendu and Pavlogiannis, Andreas and Velner, Yaron},
  isbn         = {978-1-4503-3300-9},
  journal      = {Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT },
  location     = {Mumbai, India},
  number       = {1},
  pages        = {539 -- 551},
  publisher    = {ACM},
  title        = {{Quantitative interprocedural analysis}},
  doi          = {10.1145/2676726.2676968},
  volume       = {50},
  year         = {2015},
}

@inproceedings{1605,
  abstract     = {Multiaffine hybrid automata (MHA) represent a powerful formalism to model complex dynamical systems. This formalism is particularly suited for the representation of biological systems which often exhibit highly non-linear behavior. In this paper, we consider the problem of parameter identification for MHA. We present an abstraction of MHA based on linear hybrid automata, which can be analyzed by the SpaceEx model checker. This abstraction enables a precise handling of time-dependent properties. We demonstrate the potential of our approach on a model of a genetic regulatory network and a myocyte model.},
  author       = {Bogomolov, Sergiy and Schilling, Christian and Bartocci, Ezio and Batt, Grégory and Kong, Hui and Grosu, Radu},
  location     = {Haifa, Israel},
  pages        = {19 -- 35},
  publisher    = {Springer},
  title        = {{Abstraction-based parameter synthesis for multiaffine systems}},
  doi          = {10.1007/978-3-319-26287-1_2},
  volume       = {9434},
  year         = {2015},
}

@inproceedings{1606,
  abstract     = {In this paper, we present the first steps toward a runtime verification framework for monitoring hybrid and cyber-physical systems (CPS) development tools based on randomized differential testing. The development tools include hybrid systems reachability analysis tools, model-based development environments like Simulink/Stateflow (SLSF), etc. First, hybrid automaton models are randomly generated. Next, these hybrid automaton models are translated to a number of different tools (currently, SpaceEx, dReach, Flow*, HyCreate, and the MathWorks’ Simulink/Stateflow) using the HyST source transformation and translation tool. Then, the hybrid automaton models are executed in the different tools and their outputs are parsed. The final step is the differential comparison: the outputs of the different tools are compared. If the results do not agree (in the sense that an analysis or verification result from one tool does not match that of another tool, ignoring timeouts, etc.), a candidate bug is flagged and the model is saved for future analysis by the user. The process then repeats and the monitoring continues until the user terminates the process. We present preliminary results that have been useful in identifying a few bugs in the analysis methods of different development tools, and in an earlier version of HyST.},
  author       = {Nguyen, Luan and Schilling, Christian and Bogomolov, Sergiy and Johnson, Taylor},
  booktitle    = {6th International Conference},
  isbn         = {978-3-319-23819-7},
  location     = {Vienna, Austria},
  pages        = {281 -- 286},
  publisher    = {Springer Nature},
  title        = {{Runtime verification for hybrid analysis tools}},
  doi          = {10.1007/978-3-319-23820-3_19},
  volume       = {9333},
  year         = {2015},
}

@inproceedings{1607,
  abstract     = {We consider the core algorithmic problems related to verification of systems with respect to three classical quantitative properties, namely, the mean-payoff property, the ratio property, and the minimum initial credit for energy property. The algorithmic problem given a graph and a quantitative property asks to compute the optimal value (the infimum value over all traces) from every node of the graph. We consider graphs with constant treewidth, and it is well-known that the control-flow graphs of most programs have constant treewidth. Let n denote the number of nodes of a graph, m the number of edges (for constant treewidth graphs m=O(n)) and W the largest absolute value of the weights. Our main theoretical results are as follows. First, for constant treewidth graphs we present an algorithm that approximates the mean-payoff value within a multiplicative factor of ϵ in time O(n⋅log(n/ϵ)) and linear space, as compared to the classical algorithms that require quadratic time. Second, for the ratio property we present an algorithm that for constant treewidth graphs works in time O(n⋅log(|a⋅b|))=O(n⋅log(n⋅W)), when the output is ab, as compared to the previously best known algorithm with running time O(n2⋅log(n⋅W)). Third, for the minimum initial credit problem we show that (i) for general graphs the problem can be solved in O(n2⋅m) time and the associated decision problem can be solved in O(n⋅m) time, improving the previous known O(n3⋅m⋅log(n⋅W)) and O(n2⋅m) bounds, respectively; and (ii) for constant treewidth graphs we present an algorithm that requires O(n⋅logn) time, improving the previous known O(n4⋅log(n⋅W)) bound. We have implemented some of our algorithms and show that they present a significant speedup on standard benchmarks.},
  author       = {Chatterjee, Krishnendu and Ibsen-Jensen, Rasmus and Pavlogiannis, Andreas},
  location     = {San Francisco, CA, USA},
  pages        = {140 -- 157},
  publisher    = {Springer},
  title        = {{Faster algorithms for quantitative verification in constant treewidth graphs}},
  doi          = {10.1007/978-3-319-21690-4_9},
  volume       = {9206},
  year         = {2015},
}

@inproceedings{1609,
  abstract     = {The synthesis problem asks for the automatic construction of a system from its specification. In the traditional setting, the system is “constructed from scratch” rather than composed from reusable components. However, this is rare in practice, and almost every non-trivial software system relies heavily on the use of libraries of reusable components. Recently, Lustig and Vardi introduced dataflow and controlflow synthesis from libraries of reusable components. They proved that dataflow synthesis is undecidable, while controlflow synthesis is decidable. The problem of controlflow synthesis from libraries of probabilistic components was considered by Nain, Lustig and Vardi, and was shown to be decidable for qualitative analysis (that asks that the specification be satisfied with probability 1). Our main contribution for controlflow synthesis from probabilistic components is to establish better complexity bounds for the qualitative analysis problem, and to show that the more general quantitative problem is undecidable. For the qualitative analysis, we show that the problem (i) is EXPTIME-complete when the specification is given as a deterministic parity word automaton, improving the previously known 2EXPTIME upper bound; and (ii) belongs to UP ∩ coUP and is parity-games hard, when the specification is given directly as a parity condition on the components, improving the previously known EXPTIME upper bound.},
  author       = {Chatterjee, Krishnendu and Doyen, Laurent and Vardi, Moshe},
  booktitle    = {42nd International Colloquium},
  isbn         = {978-3-662-47665-9},
  location     = {Kyoto, Japan},
  pages        = {108 -- 120},
  publisher    = {Springer Nature},
  title        = {{The complexity of synthesis from probabilistic components}},
  doi          = {10.1007/978-3-662-47666-6_9},
  volume       = {9135},
  year         = {2015},
}

@inproceedings{1610,
  abstract     = {The edit distance between two words w1, w2 is the minimal number of word operations (letter insertions, deletions, and substitutions) necessary to transform w1 to w2. The edit distance generalizes to languages L1,L2, where the edit distance is the minimal number k such that for every word from L1 there exists a word in L2 with edit distance at most k. We study the edit distance computation problem between pushdown automata and their subclasses. The problem of computing edit distance to pushdown automata is undecidable, and in practice, the interesting question is to compute the edit distance from a pushdown automaton (the implementation, a standard model for programs with recursion) to a regular language (the specification). In this work, we present a complete picture of decidability and complexity for deciding whether, for a given threshold k, the edit distance from a pushdown automaton to a finite automaton is at most k.},
  author       = {Chatterjee, Krishnendu and Henzinger, Thomas A and Ibsen-Jensen, Rasmus and Otop, Jan},
  booktitle    = {42nd International Colloquium},
  isbn         = {978-3-662-47665-9},
  location     = {Kyoto, Japan},
  number       = {Part II},
  pages        = {121 -- 133},
  publisher    = {Springer Nature},
  title        = {{Edit distance for pushdown automata}},
  doi          = {10.1007/978-3-662-47666-6_10},
  volume       = {9135},
  year         = {2015},
}

@article{1611,
  abstract     = {Biosensors for signaling molecules allow the study of physiological processes by bringing together the fields of protein engineering, fluorescence imaging, and cell biology. Construction of genetically encoded biosensors generally relies on the availability of a binding "core" that is both specific and stable, which can then be combined with fluorescent molecules to create a sensor. However, binding proteins with the desired properties are often not available in nature and substantial improvement to sensors can be required, particularly with regard to their durability. Ancestral protein reconstruction is a powerful protein-engineering tool able to generate highly stable and functional proteins. In this work, we sought to establish the utility of ancestral protein reconstruction to biosensor development, beginning with the construction of an l-arginine biosensor. l-arginine, as the immediate precursor to nitric oxide, is an important molecule in many physiological contexts including brain function. Using a combination of ancestral reconstruction and circular permutation, we constructed a Förster resonance energy transfer (FRET) biosensor for l-arginine (cpFLIPR). cpFLIPR displays high sensitivity and specificity, with a Kd of ∼14 μM and a maximal dynamic range of 35%. Importantly, cpFLIPR was highly robust, enabling accurate l-arginine measurement at physiological temperatures. We established that cpFLIPR is compatible with two-photon excitation fluorescence microscopy and report l-arginine concentrations in brain tissue.},
  author       = {Whitfield, Jason and Zhang, William and Herde, Michel and Clifton, Ben and Radziejewski, Johanna and Janovjak, Harald L and Henneberger, Christian and Jackson, Colin},
  journal      = {Protein Science},
  number       = {9},
  pages        = {1412 -- 1422},
  publisher    = {Wiley},
  title        = {{Construction of a robust and sensitive arginine biosensor through ancestral protein reconstruction}},
  doi          = {10.1002/pro.2721},
  volume       = {24},
  year         = {2015},
}

@article{1614,
  abstract     = {GABAergic perisoma-inhibiting fast-spiking interneurons (PIIs) effectively control the activity of large neuron populations by their wide axonal arborizations. It is generally assumed that the output of one PII to its target cells is strong and rapid. Here, we show that, unexpectedly, both strength and time course of PII-mediated perisomatic inhibition change with distance between synaptically connected partners in the rodent hippocampus. Synaptic signals become weaker due to lower contact numbers and decay more slowly with distance, very likely resulting from changes in GABAA receptor subunit composition. When distance-dependent synaptic inhibition is introduced to a rhythmically active neuronal network model, randomly driven principal cell assemblies are strongly synchronized by the PIIs, leading to higher precision in principal cell spike times than in a network with uniform synaptic inhibition. },
  author       = {Strüber, Michael and Jonas, Peter M and Bartos, Marlene},
  journal      = {PNAS},
  number       = {4},
  pages        = {1220 -- 1225},
  publisher    = {National Academy of Sciences},
  title        = {{Strength and duration of perisomatic GABAergic inhibition depend on distance between synaptically connected cells}},
  doi          = {10.1073/pnas.1412996112},
  volume       = {112},
  year         = {2015},
}

@article{1383,
  abstract     = {In plants, vacuolar H+-ATPase (V-ATPase) activity acidifies both the trans-Golgi network/early endosome (TGN/EE) and the vacuole. This dual V-ATPase function has impeded our understanding of how the pH homeostasis within the plant TGN/EE controls exo- and endocytosis. Here, we show that the weak V-ATPase mutant deetiolated3 (det3) displayed a pH increase in the TGN/EE, but not in the vacuole, strongly impairing secretion and recycling of the brassinosteroid receptor and the cellulose synthase complexes to the plasma membrane, in contrast to mutants lacking tonoplast-localized V-ATPase activity only. The brassinosteroid insensitivity and the cellulose deficiency defects in det3 were tightly correlated with reduced Golgi and TGN/EE motility. Thus, our results provide strong evidence that acidification of the TGN/EE, but not of the vacuole, is indispensable for functional secretion and recycling in plants.},
  author       = {Yu, Luo and Scholl, Stefan and Doering, Anett and Yi, Zhang and Irani, Niloufer and Di Rubbo, Simone and Neumetzler, Lutz and Krishnamoorthy, Praveen and Van Houtte, Isabelle and Mylle, Evelien and Bischoff, Volker and Vernhettes, Samantha and Winne, Johan and Friml, Jirí and Stierhof, York and Schumacher, Karin and Persson, Staffan and Russinova, Eugenia},
  journal      = {Nature Plants},
  number       = {7},
  publisher    = {Nature Publishing Group},
  title        = {{V-ATPase activity in the TGN/EE is required for exocytosis and recycling in Arabidopsis}},
  doi          = {10.1038/nplants.2015.94},
  volume       = {1},
  year         = {2015},
}

@phdthesis{1399,
  abstract     = {This thesis is concerned with the computation and approximation of intrinsic volumes. Given a smooth body M and a certain digital approximation of it, we develop algorithms to approximate various intrinsic volumes of M using only measurements taken from its digital approximations. The crucial idea behind our novel algorithms is to link the recent theory of persistent homology to the theory of intrinsic volumes via the Crofton formula from integral geometry and, in particular, via Euler characteristic computations. Our main contributions are a multigrid convergent digital algorithm to compute the first intrinsic volume of a solid body in R^n as well as an appropriate integration pipeline to approximate integral-geometric integrals defined over the Grassmannian manifold.},
  author       = {Pausinger, Florian},
  issn         = {2663-337X},
  pages        = {144},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{On the approximation of intrinsic volumes}},
  year         = {2015},
}

@phdthesis{1400,
  abstract     = {Cancer results from an uncontrolled growth of abnormal cells. Sequentially accumulated genetic and epigenetic alterations decrease cell death and increase cell replication. We used mathematical models to quantify the effect of driver gene mutations. The recently developed targeted therapies can lead to dramatic regressions. However, in solid cancers, clinical responses are often short-lived because resistant cancer cells evolve. We estimated that approximately 50 different mutations can confer resistance to a typical targeted therapeutic agent. We find that resistant cells are likely to be present in expanded subclones before the start of the treatment. The dominant strategy to prevent the evolution of resistance is combination therapy. Our analytical results suggest that in most patients, dual therapy, but not monotherapy, can result in long-term disease control. However, long-term control can only occur if there are no possible mutations in the genome that can cause cross-resistance to both drugs. Furthermore, we showed that simultaneous therapy with two drugs is much more likely to result in long-term disease control than sequential therapy with the same drugs. To improve our understanding of the underlying subclonal evolution we reconstruct the evolutionary history of a patient's cancer from next-generation sequencing data of spatially-distinct DNA samples. Using a quantitative measure of genetic relatedness, we found that pancreatic cancers and their metastases demonstrated a higher level of relatedness than that expected for any two cells randomly taken from a normal tissue. This minimal amount of genetic divergence among advanced lesions indicates that genetic heterogeneity, when quantitatively defined, is not a fundamental feature of the natural history of untreated pancreatic cancers. Our newly developed, phylogenomic tool Treeomics finds evidence for seeding patterns of metastases and can directly be used to discover rules governing the evolution of solid malignancies to transform cancer into a more predictable disease.},
  author       = {Reiter, Johannes},
  issn         = {2663-337X},
  pages        = {183},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{The subclonal evolution of cancer}},
  year         = {2015},
}

@phdthesis{1401,
  abstract     = {The human ability to recognize objects in complex scenes has driven research in the computer vision field over couple of decades. This thesis focuses on the object recognition task in images. That is, given the image, we want the computer system to be able to predict the class of the object that appears in the image. A recent successful attempt to bridge semantic understanding of the image perceived by humans and by computers uses attribute-based models. Attributes are semantic properties of the objects shared across different categories, which humans and computers can decide on. To explore the attribute-based models we take a statistical machine learning approach, and address two key learning challenges in view of object recognition task: learning augmented attributes as mid-level discriminative feature representation, and learning with attributes as privileged information. Our main contributions are parametric and non-parametric models and algorithms to solve these frameworks. In the parametric approach, we explore an autoencoder model combined with the large margin nearest neighbor principle for mid-level feature learning, and linear support vector machines for learning with privileged information. In the non-parametric approach, we propose a supervised Indian Buffet Process for automatic augmentation of semantic attributes, and explore the Gaussian Processes classification framework for learning with privileged information. A thorough experimental analysis shows the effectiveness of the proposed models in both parametric and non-parametric views.},
  author       = {Sharmanska, Viktoriia},
  issn         = {2663-337X},
  pages        = {144},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Learning with attributes for object recognition: Parametric and non-parametrics views}},
  doi          = {10.15479/at:ista:1401},
  year         = {2015},
}

@inproceedings{1424,
  abstract     = {We consider the problem of statistical computations with persistence diagrams, a summary representation of topological features in data. These diagrams encode persistent homology, a widely used invariant in topological data analysis. While several avenues towards a statistical treatment of the diagrams have been explored recently, we follow an alternative route that is motivated by the success of methods based on the embedding of probability measures into reproducing kernel Hilbert spaces. In fact, a positive definite kernel on persistence diagrams has recently been proposed, connecting persistent homology to popular kernel-based learning techniques such as support vector machines. However, important properties of that kernel enabling a principled use in the context of probability measure embeddings remain to be explored. Our contribution is to close this gap by proving universality of a variant of the original kernel, and to demonstrate its effective use in twosample hypothesis testing on synthetic as well as real-world data.},
  author       = {Kwitt, Roland and Huber, Stefan and Niethammer, Marc and Lin, Weili and Bauer, Ulrich},
  location     = {Montreal, Canada},
  pages        = {3070 -- 3078},
  publisher    = {Neural Information Processing Systems},
  title        = {{Statistical topological data analysis-A kernel perspective}},
  volume       = {28},
  year         = {2015},
}

@inproceedings{1425,
  abstract     = {In this work we aim at extending the theoretical foundations of lifelong learning. Previous work analyzing this scenario is based on the assumption that learning tasks are sampled i.i.d. from a task environment or limited to strongly constrained data distributions. Instead, we study two scenarios when lifelong learning is possible, even though the observed tasks do not form an i.i.d. sample: first, when they are sampled from the same environment, but possibly with dependencies, and second, when the task environment is allowed to change over time in a consistent way. In the first case we prove a PAC-Bayesian theorem that can be seen as a direct generalization of the analogous previous result for the i.i.d. case. For the second scenario we propose to learn an inductive bias in form of a transfer procedure. We present a generalization bound and show on a toy example how it can be used to identify a beneficial transfer algorithm.},
  author       = {Pentina, Anastasia and Lampert, Christoph},
  location     = {Montreal, Canada},
  pages        = {1540 -- 1548},
  publisher    = {Neural Information Processing Systems},
  title        = {{Lifelong learning with non-i.i.d. tasks}},
  volume       = {2015},
  year         = {2015},
}

@inproceedings{1430,
  abstract     = {Evolutionary algorithms (EAs) form a popular optimisation paradigm inspired by natural evolution. In recent years the field of evolutionary computation has developed a rigorous analytical theory to analyse their runtime on many illustrative problems. Here we apply this theory to a simple model of natural evolution. In the Strong Selection Weak Mutation (SSWM) evolutionary regime the time between occurrence of new mutations is much longer than the time it takes for a new beneficial mutation to take over the population. In this situation, the population only contains copies of one genotype and evolution can be modelled as a (1+1)-type process where the probability of accepting a new genotype (improvements or worsenings) depends on the change in fitness. We present an initial runtime analysis of SSWM, quantifying its performance for various parameters and investigating differences to the (1+1) EA. We show that SSWM can have a moderate advantage over the (1+1) EA at crossing fitness valleys and study an example where SSWM outperforms the (1+1) EA by taking advantage of information on the fitness gradient.},
  author       = {Paixao, Tiago and Sudholt, Dirk and Heredia, Jorge and Trubenova, Barbora},
  booktitle    = {Proceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation},
  location     = {Madrid, Spain},
  pages        = {1455 -- 1462},
  publisher    = {ACM},
  title        = {{First steps towards a runtime comparison of natural and artificial evolution}},
  doi          = {10.1145/2739480.2754758},
  year         = {2015},
}

@article{9532,
  abstract     = {Genomic imprinting, an inherently epigenetic phenomenon defined by parent of origin-dependent gene expression, is observed in mammals and flowering plants. Genome-scale surveys of imprinted expression and the underlying differential epigenetic marks have led to the discovery of hundreds of imprinted plant genes and confirmed DNA and histone methylation as key regulators of plant imprinting. However, the biological roles of the vast majority of imprinted plant genes are unknown, and the evolutionary forces shaping plant imprinting remain rather opaque. Here, we review the mechanisms of plant genomic imprinting and discuss theories of imprinting evolution and biological significance in light of recent findings.},
  author       = {Rodrigues, Jessica A. and Zilberman, Daniel},
  issn         = {1549-5477},
  journal      = {Genes and Development},
  number       = {24},
  pages        = {2517–2531},
  publisher    = {Cold Spring Harbor Laboratory Press},
  title        = {{Evolution and function of genomic imprinting in plants}},
  doi          = {10.1101/gad.269902.115},
  volume       = {29},
  year         = {2015},
}

@article{12196,
  abstract     = {SNC1 (SUPPRESSOR OF NPR1, CONSTITUTIVE 1) is one of a suite of intracellular Arabidopsis NOD-like receptor (NLR) proteins which, upon activation, result in the induction of defense responses. However, the molecular mechanisms underlying NLR activation and the subsequent provocation of immune responses are only partially characterized. To identify negative regulators of NLR-mediated immunity, a forward genetic screen was undertaken to search for enhancers of the dwarf, autoimmune gain-of-function snc1 mutant. To avoid lethality resulting from severe dwarfism, the screen was conducted using mos4 (modifier of snc1, 4) snc1 plants, which display wild-type-like morphology and resistance. M2 progeny were screened for mutant, snc1-enhancing (muse) mutants displaying a reversion to snc1-like phenotypes. The muse9 mos4 snc1 triple mutant was found to exhibit dwarf morphology, elevated expression of the pPR2-GUS defense marker reporter gene and enhanced resistance to the oomycete pathogen Hyaloperonospora arabidopsidis Noco2. Via map-based cloning and Illumina sequencing, it was determined that the muse9 mutation is in the gene encoding the SWI/SNF chromatin remodeler SYD (SPLAYED), and was thus renamed syd-10. The syd-10 single mutant has no observable alteration from wild-type-like resistance, although the syd-4 T-DNA insertion allele displays enhanced resistance to the bacterial pathogen Pseudomonas syringae pv. maculicola ES4326. Transcription of SNC1 is increased in both syd-4 and syd-10. These data suggest that SYD plays a subtle, specific role in the regulation of SNC1 expression and SNC1-mediated immunity. SYD may work with other proteins at the chromatin level to repress SNC1 transcription; such regulation is important for fine-tuning the expression of NLR-encoding genes to prevent unpropitious autoimmunity.},
  author       = {Johnson, Kaeli C.M. and Xia, Shitou and Feng, Xiaoqi and Li, Xin},
  issn         = {0032-0781},
  journal      = {Plant and Cell Physiology},
  keywords     = {Cell Biology, Plant Science, Physiology, General Medicine},
  number       = {8},
  pages        = {1616--1623},
  publisher    = {Oxford University Press},
  title        = {{The chromatin remodeler SPLAYED negatively regulates SNC1-mediated immunity}},
  doi          = {10.1093/pcp/pcv087},
  volume       = {56},
  year         = {2015},
}

@inproceedings{12881,
  author       = {Martius, Georg S and Olbrich, Eckehard},
  booktitle    = {Proceedings of the 13th European Conference on Artificial Life},
  isbn         = {9780262330275},
  location     = {York, United Kingdom},
  pages        = {78},
  publisher    = {MIT Press},
  title        = {{Quantifying self-organizing behavior of autonomous robots}},
  doi          = {10.7551/978-0-262-33027-5-ch018},
  year         = {2015},
}

@misc{9711,
  author       = {Chevereau, Guillaume and Lukacisinova, Marta and Batur, Tugce and Guvenek, Aysegul and Ayhan, Dilay Hazal and Toprak, Erdal and Bollenbach, Mark Tobias},
  publisher    = {Public Library of Science},
  title        = {{Excel file containing the raw data for all figures}},
  doi          = {10.1371/journal.pbio.1002299.s001},
  year         = {2015},
}

@misc{9712,
  author       = {Tugrul, Murat and Paixao, Tiago and Barton, Nicholas H and Tkačik, Gašper},
  publisher    = {Public Library of Science},
  title        = {{Other fitness models for comparison & for interacting TFBSs}},
  doi          = {10.1371/journal.pgen.1005639.s001},
  year         = {2015},
}