Studying Evolutionary Change: Transdisciplinary Advances in Understanding and Measuring Evolution

Evolutionary processes can be found in almost any historical, i.e. evolving, system that erroneously copies from the past. Well studied examples do not only originate in evolutionary biology but also in historical linguistics. Yet an approach that would bind together studies of such evolving systems is still elusive. This thesis is an attempt to narrowing down this gap to some extend. An evolving system can be described using characters that identify their changing features. While the problem of a proper choice of characters is beyond the scope of this thesis and remains in the hands of experts we concern ourselves with some theoretical as well data driven approaches. Having a well chosen set of characters describing a system of different entities such as homologous genes, i.e. genes of same origin in different species, we can build a phylogenetic tree. Consider the special case of gene clusters containing paralogous genes, i.e. genes of same origin within a species usually located closely, such as the well known HOX cluster. These are formed by step- wise duplication of its members, often involving unequal crossing over forming hybrid genes. Gene conversion and possibly other mechanisms of concerted evolution further obfuscate phylogenetic relationships. Hence, it is very difficult or even impossible to disentangle the detailed history of gene duplications in gene clusters. Expanding gene clusters that use unequal crossing over as proposed by Walter Gehring leads to distinctive patterns of genetic distances. We show that this special class of distances helps in extracting phylogenetic information from the data still. Disregarding genome rearrangements, we find that the shortest Hamiltonian path then coincides with the ordering of paralogous genes in a cluster. This observation can be used to detect ancient genomic rearrangements of gene clus- ters and to distinguish gene clusters whose evolution was dominated by unequal crossing over within genes from those that expanded through other mechanisms. While the evolution of DNA or protein sequences is well studied and can be formally described, we find that this does not hold for other systems such as language evolution. This is due to a lack of detectable mechanisms that drive the evolutionary processes in other fields. Hence, it is hard to quantify distances between entities, e.g. languages, and therefore the characters describing them. Starting out with distortions of distances, we first see that poor choices of the distance measure can lead to incorrect phylogenies. Given that phylogenetic inference requires additive metrics we can infer the correct phylogeny from a distance matrix D if there is a monotonic, subadditive function ζ such that ζ^−1(D) is additive. We compute the metric-preserving transformation ζ as the solution of an optimization problem. This result shows that the problem of phylogeny reconstruction is well defined even if a detailed mechanistic model of the evolutionary process is missing. Yet, this does not hinder studies of language evolution using automated tools. As the amount of available and large digital corpora increased so did the possibilities to study them automatically. The obvious parallels between historical linguistics and phylogenetics lead to many studies adapting bioinformatics tools to fit linguistics means. Here, we use jAlign to calculate bigram alignments, i.e. an alignment algorithm that operates with regard to adjacency of letters. Its performance is tested in different cognate recognition tasks. Using pairwise alignments one major obstacle is the systematic errors they make such as underestimation of gaps and their misplacement. Applying multiple sequence alignments instead of a pairwise algorithm implicitly includes more evolutionary information and thus can overcome the problem of correct gap placement. They can be seen as a generalization of the string-to-string edit problem to more than two strings. With the steady increase in computational power, exact, dynamic programming solutions have become feasible in practice also for 3- and 4-way alignments. For the pairwise (2-way) case, there is a clear distinction between local and global alignments. As more sequences are consid- ered, this distinction, which can in fact be made independently for both ends of each sequence, gives rise to a rich set of partially local alignment problems. So far these have remained largely unexplored. Thus, a general formal frame- work that gives raise to a classification of partially local alignment problems is introduced. It leads to a generic scheme that guides the principled design of exact dynamic programming solutions for particular partially local alignment problems

Economic potential of demand side management based on smart metering of youth hostels in Germany

Additional electricity meters behind the grid access point can improve understanding of energy consumption patterns and thus, adjust consumption behavior. For this study, smart meters were installed in three hostels, out of which two are analyzed further in this paper. Starting from an onsite inspection, all appliances were assigned to reasonable groups for sub-metering. Based on data for the year 2021, the sites are characterized according to the sub-metering concept. In addition, load profiles for type-days are derived, which allows to establish a baseload during COVID lockdown and compare it to consumption patterns for normal occupation. In the prescriptive part, the demand profiles are analyzed regarding their economic potential for load shifting. Consumption data for one week with normal occupation is used as input for techno-economic modeling. The mixed-integer model minimizes electricity purchasing costs for different scenarios including dynamic tariffs and onsite generation from photovoltaics

LabChain: an Interactive Prototype for Synthetic Peer-to-Peer Trade Research in Experimental Energy Economics

Blockchain-based peer-to-peer (P2P) electricity markets received considerable attention in the past years, leading to a rich variety of proposed market designs. Yet, little comparability and consensus exists on optimal market design, also due to a lack of common evaluation and benchmarking infrastructure. This article describes LabChain, an interactive prototype as research infrastructure for conducting experiments in (simulated) P2P electricity markets involving real human actors. The software stack comprises: (i) an (open) data layer for experiment configuration, (ii) a blockchain layer to reliably document bids and transactions, (iii) an experiment coordination layer and (iv) a user interface layer for participant interactions. As evaluation environment for human interactions within a laboratory setting, researchers can investigate patterns based on energy system and market setup and can compare and evaluate designs under real human behavior allowing alignment of intentions and outcomes. This contributes to the evaluation and benchmarking infrastructure discourse

Studying Evolutionary Change: Transdisciplinary Advances in Understanding and Measuring Evolution

Evolutionary processes can be found in almost any historical, i.e. evolving, system that erroneously copies from the past. Well studied examples do not only originate in evolutionary biology but also in historical linguistics. Yet an approach that would bind together studies of such evolving systems is still elusive. This thesis is an attempt to narrowing down this gap to some extend. An evolving system can be described using characters that identify their changing features. While the problem of a proper choice of characters is beyond the scope of this thesis and remains in the hands of experts we concern ourselves with some theoretical as well data driven approaches. Having a well chosen set of characters describing a system of different entities such as homologous genes, i.e. genes of same origin in different species, we can build a phylogenetic tree. Consider the special case of gene clusters containing paralogous genes, i.e. genes of same origin within a species usually located closely, such as the well known HOX cluster. These are formed by step- wise duplication of its members, often involving unequal crossing over forming hybrid genes. Gene conversion and possibly other mechanisms of concerted evolution further obfuscate phylogenetic relationships. Hence, it is very difficult or even impossible to disentangle the detailed history of gene duplications in gene clusters. Expanding gene clusters that use unequal crossing over as proposed by Walter Gehring leads to distinctive patterns of genetic distances. We show that this special class of distances helps in extracting phylogenetic information from the data still. Disregarding genome rearrangements, we find that the shortest Hamiltonian path then coincides with the ordering of paralogous genes in a cluster. This observation can be used to detect ancient genomic rearrangements of gene clus- ters and to distinguish gene clusters whose evolution was dominated by unequal crossing over within genes from those that expanded through other mechanisms. While the evolution of DNA or protein sequences is well studied and can be formally described, we find that this does not hold for other systems such as language evolution. This is due to a lack of detectable mechanisms that drive the evolutionary processes in other fields. Hence, it is hard to quantify distances between entities, e.g. languages, and therefore the characters describing them. Starting out with distortions of distances, we first see that poor choices of the distance measure can lead to incorrect phylogenies. Given that phylogenetic inference requires additive metrics we can infer the correct phylogeny from a distance matrix D if there is a monotonic, subadditive function ζ such that ζ^−1(D) is additive. We compute the metric-preserving transformation ζ as the solution of an optimization problem. This result shows that the problem of phylogeny reconstruction is well defined even if a detailed mechanistic model of the evolutionary process is missing. Yet, this does not hinder studies of language evolution using automated tools. As the amount of available and large digital corpora increased so did the possibilities to study them automatically. The obvious parallels between historical linguistics and phylogenetics lead to many studies adapting bioinformatics tools to fit linguistics means. Here, we use jAlign to calculate bigram alignments, i.e. an alignment algorithm that operates with regard to adjacency of letters. Its performance is tested in different cognate recognition tasks. Using pairwise alignments one major obstacle is the systematic errors they make such as underestimation of gaps and their misplacement. Applying multiple sequence alignments instead of a pairwise algorithm implicitly includes more evolutionary information and thus can overcome the problem of correct gap placement. They can be seen as a generalization of the string-to-string edit problem to more than two strings. With the steady increase in computational power, exact, dynamic programming solutions have become feasible in practice also for 3- and 4-way alignments. For the pairwise (2-way) case, there is a clear distinction between local and global alignments. As more sequences are consid- ered, this distinction, which can in fact be made independently for both ends of each sequence, gives rise to a rich set of partially local alignment problems. So far these have remained largely unexplored. Thus, a general formal frame- work that gives raise to a classification of partially local alignment problems is introduced. It leads to a generic scheme that guides the principled design of exact dynamic programming solutions for particular partially local alignment problems

Bigram Alignment and its Application in Historical Linguistics

Die vorliegende Arbeit beschäftigt sich mit der Frage nach dem optimalen Scoring-Modell, unter Betrachtung von Bigrammen. Dazu sollen in den ersten Kapiteln Grundlagen erklärt werden, auf welche sich Auswertung und Diskussion beziehen. Nach einer kurzen „Einleitung“ werden im Kapitel „Linguistischer Hintergrund“ ein Einblick in die vergleichende Sprachwissenschaft gegeben und reguläre Wortveränderungen eingeführt, sowie verschiedene frühe Wortalignment-Algorithmen vorgestellt. Der „Bioinformatische Hintergrund“ befasst sich mit komplexeren Alignierungsalgorithmen, wie die nach Needleman-Wunsch, Smith-Waterman und Gotoh. Im „Methoden“-Teil werden dann zum einen die den Algorithmen zugrundeliegenden Scoring-Modelle erläutert und zum anderen ein Einblick in die Theorie der Formalen Sprachen gewährt. Auf die im Verlauf der Arbeit entstandenen Ergebnisse wird dann in „Auswertung“ und „Diskussion“ eingegangen und Bezüge zur Linguistik hergestellt

Studying Evolutionary Change: Transdisciplinary Advances in Understanding and Measuring Evolution

Evolutionary processes can be found in almost any historical, i.e. evolving, system that erroneously copies from the past. Well studied examples do not only originate in evolutionary biology but also in historical linguistics. Yet an approach that would bind together studies of such evolving systems is still elusive. This thesis is an attempt to narrowing down this gap to some extend. An evolving system can be described using characters that identify their changing features. While the problem of a proper choice of characters is beyond the scope of this thesis and remains in the hands of experts we concern ourselves with some theoretical as well data driven approaches. Having a well chosen set of characters describing a system of different entities such as homologous genes, i.e. genes of same origin in different species, we can build a phylogenetic tree. Consider the special case of gene clusters containing paralogous genes, i.e. genes of same origin within a species usually located closely, such as the well known HOX cluster. These are formed by step- wise duplication of its members, often involving unequal crossing over forming hybrid genes. Gene conversion and possibly other mechanisms of concerted evolution further obfuscate phylogenetic relationships. Hence, it is very difficult or even impossible to disentangle the detailed history of gene duplications in gene clusters. Expanding gene clusters that use unequal crossing over as proposed by Walter Gehring leads to distinctive patterns of genetic distances. We show that this special class of distances helps in extracting phylogenetic information from the data still. Disregarding genome rearrangements, we find that the shortest Hamiltonian path then coincides with the ordering of paralogous genes in a cluster. This observation can be used to detect ancient genomic rearrangements of gene clus- ters and to distinguish gene clusters whose evolution was dominated by unequal crossing over within genes from those that expanded through other mechanisms. While the evolution of DNA or protein sequences is well studied and can be formally described, we find that this does not hold for other systems such as language evolution. This is due to a lack of detectable mechanisms that drive the evolutionary processes in other fields. Hence, it is hard to quantify distances between entities, e.g. languages, and therefore the characters describing them. Starting out with distortions of distances, we first see that poor choices of the distance measure can lead to incorrect phylogenies. Given that phylogenetic inference requires additive metrics we can infer the correct phylogeny from a distance matrix D if there is a monotonic, subadditive function ζ such that ζ^−1(D) is additive. We compute the metric-preserving transformation ζ as the solution of an optimization problem. This result shows that the problem of phylogeny reconstruction is well defined even if a detailed mechanistic model of the evolutionary process is missing. Yet, this does not hinder studies of language evolution using automated tools. As the amount of available and large digital corpora increased so did the possibilities to study them automatically. The obvious parallels between historical linguistics and phylogenetics lead to many studies adapting bioinformatics tools to fit linguistics means. Here, we use jAlign to calculate bigram alignments, i.e. an alignment algorithm that operates with regard to adjacency of letters. Its performance is tested in different cognate recognition tasks. Using pairwise alignments one major obstacle is the systematic errors they make such as underestimation of gaps and their misplacement. Applying multiple sequence alignments instead of a pairwise algorithm implicitly includes more evolutionary information and thus can overcome the problem of correct gap placement. They can be seen as a generalization of the string-to-string edit problem to more than two strings. With the steady increase in computational power, exact, dynamic programming solutions have become feasible in practice also for 3- and 4-way alignments. For the pairwise (2-way) case, there is a clear distinction between local and global alignments. As more sequences are consid- ered, this distinction, which can in fact be made independently for both ends of each sequence, gives rise to a rich set of partially local alignment problems. So far these have remained largely unexplored. Thus, a general formal frame- work that gives raise to a classification of partially local alignment problems is introduced. It leads to a generic scheme that guides the principled design of exact dynamic programming solutions for particular partially local alignment problems

Convexity deficit of benzenoids

In 2012, a family of benzenoids was introduced by Cruz, Gutman, and Rada, which they called convex benzenoids. In this paper we introduce the convexity deficit, a new topological index intended for benzenoids and, more generally, fusenes. This index measures by how much a given fusene departs from convexity. It is defined in terms of the boundary-edges code. In particular, convex benzenoids are exactly the benzenoids having convexity deficit equal to 0. Quasi-convex benzenoids form the family of non-convex benzenoids that are closest to convex, i.e., they have convexity deficit equal to 1. Finally, we investigate convexity deficit of several important families of benzenoids. This work is licensed under a Creative Commons Attribution 4.0 International License

Orthologs, turn-over, and remolding of tRNAs in primates and fruit flies

Background: Transfer RNAs (tRNAs) are ubiquitous in all living organism. They implement the genetic code so that most genomes contain distinct tRNAs for almost all 61 codons. They behave similar to mobile elements and proliferate in genomes spawning both local and non-local copies. Most tRNA families are therefore typically present as multicopy genes. The members of the individual tRNA families evolve under concerted or rapid birth-death evolution, so that paralogous copies maintain almost identical sequences over long evolutionary time-scales. To a good approximation these are functionally equivalent. Individual tRNA copies thus are evolutionary unstable and easily turn into pseudogenes and disappear. This leads to a rapid turnover of tRNAs and often large differences in the tRNA complements of closely related species. Since tRNA paralogs are not distinguished by sequence, common methods cannot not be used to establish orthology between tRNA genes. Results: In this contribution we introduce a general framework to distinguish orthologs and paralogs in gene families that are subject to concerted evolution. It is based on the use of uniquely aligned adjacent sequence elements as anchors to establish syntenic conservation of sequence intervals. In practice, anchors and intervals can be extracted from genome-wide multiple sequence alignments. Syntenic clusters of concertedly evolving genes of different families can then be subdivided by list alignments, leading to usually small clusters of candidate co-orthologs. On the basis of recent advances in phylogenetic combinatorics, these candidate clusters can be further processed by cograph editing to recover their duplication histories. We developed a workflow that can be conceptualized as stepwise refinement of a graph of homologous genes. We apply this analysis strategy with different types of synteny anchors to investigate the evolution of tRNAs in primates and fruit flies. We identified a large number of tRNA remolding events concentrated at the tips of the phylogeny. With one notable exception all phylogenetically old tRNA remoldings do not change the isoacceptor class. Conclusions: Gene families evolving under concerted evolution are not amenable to classical phylogenetic analyses since paralogs maintain identical, species-specific sequences, precluding the estimation of correct gene trees from sequence differences. This leaves conservation of syntenic arrangements with respect to "anchor elements" that are not subject to concerted evolution as the only viable source of phylogenetic information. We have demonstrated here that a purely synteny-based analysis of tRNA gene histories is indeed feasible. Although the choice of synteny anchors influences the resolution in particular when tight gene clusters are present, and the quality of sequence alignments, genome assemblies, and genome rearrangements limits the scope of the analysis, largely coherent results can be obtained for tRNAs. In particular, we conclude that a large fraction of the tRNAs are recent copies. This proliferation is compensated by rapid pseudogenization as exemplified by many very recent alloacceptor remoldings