This paper explores utilization of bots created to play as participants in two games that have relevance in the field of economics. The first game is an iterated version of the prisoner's dilemma that has relevance to decisions requiring trust while conducting business and involves a binary decision. The simulation examines one dimension of the Myers-Briggs personality type and its potential association with strategies that may be employed during an iterated version of the game, leading to different levels of performance. A web-based bot is used for such simulation. Results appear to support the possibility of exploiting personality type in this dimension in the context of similar circumstances. The second game is an iterated power to take game that simulates interactions between taxing authorities (takers) and taxpayers (responders), and involves a continuous set of possible decisions for each stage of the game. A specific Myers-Briggs personality type of specified extremity is embedded into each player bot by randomly generating answers to a version of the Myers-Briggs Type Indicator. These answers are individually associated with preferences and strategies that allow the bots to react to the changing game state according to their personality type. This paper explores the combination of, among other things, team sizes, initial conditions of income tax rates in some of the major economies on different continents, adjudication methods for group decisions, as well as personality type extremity. In a large number of simulations, various group compositions in terms of MBTI personality type are matched up against each other under these conditions, and their performance is ranked for each role. Results appear to suggest that selective recruitment practices based on personality type can enhance performance of both takers and responders and may lead to improvements of certain aspects of economic conditions.
Proteins rarely carry out their cellular functions in isolation. Instead, eukaryotic proteins engage in about six interactions with other proteins on average. The aggregated protein interactome of an organism forms a “hairy ball”-type protein-protein interaction (PPI) network. Yet, in a typical human cell, only about half of all proteins are expressed at a particular time. Hence, it has become common practice to prune the full PPI network to the subset of expressed proteins. If RNAseq data is available, one can further resolve the specific protein isoforms present in a cell or tissue. Here, we review various approaches, software tools and webservices that enable users to construct context-specific or tissue-specific PPI networks and how these are rewired between two cellular conditions. We illustrate their different functionalities on the example of the interactions involving the human TNR6 protein. In an outlook, we describe how PPI networks may be integrated with epigenetic data or with data on the activity of splicing factors.
Surface pockets, cavities, and tunnels in the 3D structures of proteins play integral functional roles such as enabling enzymatic catalysis, ligand binding, or transport of ions or small molecules across biomembranes. ProPores2 facilitates understanding and analysis of these processes by identifying pores and lining residues, determining their axes, and opening closed connections via side-chain rotation. The fast stand-alone tool introduces a novel mode for pore identification, improved axis determination, and additional features such as parallel batch processing and a graphical user interface. The new web service features an integrated and customizable protein viewer with an option to analyze and view more than one structure at once. This feature facilitates side-by-side comparisons of pores in different conformations of the same protein or of identified pores before and after opening gates within the same protein. ProPores2 is freely and publicly available at https://service.bioinformatik.uni-saarland.de/propores.
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