Multi-criteria decision-analysis (MCDA) is a popular field of study with implementations in various areas, such as supply chain management, logistics, engineering, health, sustainable development, to name a few. The normalization of the data considered in such challenges (decision matrix) is an essential step of many MCDA methods. Different normalization techniques can influence the results obtained, and hence, generate different final rankings. In this paper, the investigation of normalization effects is conducted in the PROMETHEE II method. Five different normalization methods were used and additionally, the case without normalization was examined. In order to compare the influence of various normalization methods, an empirical study on the selection of the location of the airport was analyzed, with ten alternatives and seven criteria. The outcomes of investigation of normalization effects in regard to the PROMETHEE II method prove that they do have an impact on the final rankings.

Multi-criteria decision-analysis (MCDA) methods have been widely applied by many researchers in various fields of study. One of the numerous MCDA methods, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) under fuzzy environment, namely fuzzy TOPSIS, has been successfully applied in many practical, real-world challenges. This paper provides a short review of fuzzy TOPSIS applications. The research is based on 25 studies conducted in the years 2009 - 2018. Most relevant and most cited papers concerned with fuzzy TOPSIS technique were analyzed and categorized into application areas, such as supply chain, environment, energy sources, business, healthcare. Fuzzy TOPSIS implementations are examined and compared by approaches used, such as fuzzy sets, hesitant fuzzy sets or intuitionistic fuzzy sets, by other methods combined with fuzzy TOPSIS, such as fuzzy Analytic Hierarchic Process (AHP) or enhancements for group decision-making and by a number of alternatives and criteria used. Finally, insights into ongoing trends, most popular approaches, and directions of study concerning the fuzzy TOPSIS method are presented.

Many people, organizations and managers try to assess the performance of the football teams and seek new improved approaches. Rankings are an unavoidable part of the football world, where high competitiveness and efficiency is a natural factor. One of the techniques to deal with such problems is the use of multi-criteria decision-analysis methods (MCDA), offering an effective approach to not only ranking but also assessing, selecting and sorting given alternatives. In this paper, the Characteristic Objects METhod (COMET) is used in order to create a performance ranking of the top-tier football clubs. The assessment model is identified and compared with the existing benchmark ranking by the Spearman’s rank correlation coefficient.

SUMMARY: Rapid expansion of available data about G Protein Coupled Receptor (GPCR) dimers/oligomers over the past few years requires an effective system to organize this information electronically. Based on an ontology derived from a community dialog involving colleagues using experimental and computational methodologies, we developed the GPCR-Oligomerization Knowledge Base (GPCR-OKB). GPCR-OKB is a system that supports browsing and searching for GPCR oligomer data. Such data were manually derived from the literature. While focused on GPCR oligomers, GPCR-OKB is seamlessly connected to GPCRDB, facilitating the correlation of information about GPCR protomers and oligomers. AVAILABILITY AND IMPLEMENTATION: The GPCR-OKB web application is freely available at http://www.gpcr-okb.org

BACKGROUND: G Protein-Coupled Receptors (GPCRs) are a large and diverse family of membrane proteins whose members participate in the regulation of most cellular and physiological processes and therefore represent key pharmacological targets. Although several bioinformatics resources support research on GPCRs, most of these have been designed based on the traditional assumption that monomeric GPCRs constitute the functional receptor unit. The increase in the frequency and number of reports about GPCR dimerization/oligomerization and the implication of oligomerization in receptor function makes necessary the ability to store and access information about GPCR dimers/oligomers electronically. RESULTS: We present here the requirements and ontology (the information scheme to describe oligomers and associated concepts and their relationships) for an information system that can manage the elements of information needed to describe comprehensively the phenomena of both homo- and hetero-oligomerization of GPCRs. The comprehensive information management scheme that we plan to use for the development of an intuitive and user-friendly GPCR-Oligomerization Knowledge Base (GPCR-OKB) is the result of a community dialog involving experimental and computational colleagues working on GPCRs. CONCLUSION: Our long term goal is to disseminate to the scientific community organized, curated, and detailed information about GPCR dimerization/oligomerization and its related structural context. This information will be reported as close to the data as possible so the user can make his own judgment on the conclusions drawn for a particular study. The requirements and ontology described here will facilitate the development of future information systems for GPCR oligomers that contain both computational and experimental information about GPCR oligomerization. This information is freely accessible at http://www.gpcr-okb.org.