Cooperative game for biotechnology and implementation in C++
Short Description
Cooperative game theory and power indices (see e.g. [1]) are techniques traditionally used to analyse voting in committees (see e.g. [2], [3]) or influence in networks (see e.g. [4], [5]). In this project we applied these techniques to data from biotechnology and computational medicine (see e.g. [6,7,8]).
About the Project
The idea of this project was to both study and efficiently implement approaches for applying concepts from cooperative game theory to the analysis of genetic datasets from some of Stefano Moretti’s publications in this field [6,7,8]. In brief, the challenge is to analyze large amounts of genetic data, always bearing in mind no single gene can explain the cause of a certain condition or disease. Instead, we use approaches from game theory to identify groups of important genes.
Stefano Moretti kindly agreed to provide co-supervision for this project and established a precious contact to his coauthor Min Woo Sun, a doctoral student at Stanford University who joined the team of supervisors. The 9 hour time difference between Stanford and Kempten meant that we had to reschedule our virtual meetings to the evening hours of Central European time, but the Kempten students always kept up spirits and never lost their enthusiasm. We are still very grateful to Min for his invaluable input and his efforts on this project as we could never have succeeded without his insightful knowledge on bioinformatics.
The student team produced innovative software in both R and C++ handling large genetic datasets, including colon cancer data [8] and an iteraction network between genes from blood cells of
children from the Teplice region in the Czech Republic, formerly an area with high levels of carcinogenic air pollutant, taken from the paper by Moretti et al. (2010) [6] .
Authors
Kempten students taking part in the project: Fabian Brosda, Marc-Aurel Fritz, Felix Kleis
Supervisors: Jochen Staudacher (Kempten), Min Woo Sun (Stanford University), Stefano Moretti (Université Paris-Dauphine)
Faculty: Computer Science, M.Sc. in Computer Science (Informatik)
Date of realisation: WS 2021/22
References
[1] S.R. Chakravarty, M. Mitra, P. Sarkar, A Course on Cooperative Game Theory. Cambridge University Press, 2015.
[2] E. Algaba, J.M. Bilbao, J.R. Fernandéz, The distribution of power in the European Constitution, European Journal of Operational Research, 2007, 176 (3), 1752-66.
[3] L.Á. Kóczy, Beyond Lisbon: Demographic trends and voting power in the European Union Council of Ministers, Mathematical Social Sciences, 2012, 63 (2), 152-8.
[4] C. Bertini, J. Mercik, I. Stach, Indirect Control and Power, Operations Research and Decisions, 26 (2), pp. 7-30, 2016.
[5] M.J. Holler, F. Rupp, Power in networks: A PGI Analysis of Krackhardt’s Kite Network, Springer Lecture Notes in Computer Science 11890, 2019, 21-34.
[6] S. Moretti, V. Fragnelli, F. Patrone, S. Bonassi, Using coalitional games on biological networks to measure centrality and power of genes, Bioinformatics, 26(21), 2721-30, 2010.
[7] Lucchetti, R., Moretti, S., Patrone, F., Radrizzani, P. (2010) The Shapley and Banzhaf values in microarray games, Computers & Operations Research 37(8), 1406-1412.
[8] P. Neog Bora, V.J. Baruah, S. Borkotokey, L. Gogoi, P. Mahanta, A. Sarmah, R. Kumar, S. Moretti, Identifying the Salient Genes in Microarray Data: A Novel Game Theoretic Model for the Co-Expression Network, Diagnostics, 10(8), 586, 2020.