Information Theory and Algorithmic Complexity for Network Biology
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Complexity".
Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 423
Special Issue Editors
2. European Center for Bioinformatics and Genomics, 60-965 Poznan, Poland
3. Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
Interests: operational research; scheduling theory; bioinformatics; combinatorial optimization; computational complexity
Interests: operational research; combinatorial optimization; computational complexity; graph theory; scheduling theory; computational and systems biology; DNA and quantum computing
Interests: operations research; discrete optimization; scheduling; algorithmic graph theory; bioinformatics; quantum computing
2. Institute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland
3. Faculty of Electrical Engineering, Gdynia Maritime University, 81-225 Gdynia, Poland
Interests: computational biology
Special Issue Information
Dear Colleagues,
Living organisms and their functional modules are complex systems. They are composed of a number of elementary building blocks connected by dense networks of interactions. From the structure of these networks, many properties—including the most crucial ones—of biological systems follow. Hence, in order to fully understand the mechanisms governing the living world it is not sufficient to study the elementary biological building blocks separately—this study should be complemented by an analysis of the structure of the network of interactions among them. One of the approaches to this problem is to develop models of biological systems in the form of graphs or networks, which in a natural way can describe the structure of the analyzed biological system.
Two of the fundamental properties of biological systems are their complexity and ability to process information. Good models of such systems should allow the discovery of important and previously unknown properties of analyzed phenomena. Hence, on one hand, these models should reflect the complexity and information-based characteristics of the systems, and on the other they should analyze the model from information-theoretic and complexity perspectives, ideally yielding interesting conclusions and aiding the discovery of mechanisms of the living world. However, in order for such an approach to be effective, proper advanced methods must be used.
This Special Issue is intended to be a forum for presenting theoretical ideas based on information theory and complexity (especially the algorithmic one) for the analysis of complex biological systems and its applications.
Prof. Dr. Jacek Blazewicz
Prof. Dr. Piotr Formanowicz
Prof. Dr. Krzysztof Giaro
Dr. Agnieszka Rybarczyk
Guest Editors
Manuscript Submission Information
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Keywords
- complex biological systems
- networks
- graphs
- complexity
- information theory
- algorithms
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