The DNA from a Communications and Information Theoretic Perspective

  • Beyond enabling the successful development of communication engineering, information theory has far-reaching applications in other disciplines, including molecular biology. Information theory has been effectively applied for analyzing and modeling biological systems and processes. Following the same framework, in this thesis, three related but distinct topics are studied. First, we modeled the transmission of genetic information assuming a codon-based mutation matrix as a communication channel and performed capacity computations. Furthermore, the severity of codon substitution errors was assessed by comparing mutation probabilities with chemical properties of amino acids using a dimension reduction technique. The second topic deals with the analysis of the relationship between the digital and analog information in bacterial genomes. The latter represents the three-dimensional information encoded by the physicochemical properties of the DNA. Here, the analog information is associated with thermodynamic stability. In addition, the spatial genomic sequence organization is studied in relation to selected functional classes of genes. Finally, a novel method of essential gene prediction based on machine-learning is proposed. Information-theoretic measures have been used as features and essentiality predictions were performed in both prokaryotes and eukaryotes. The obtained results show that gene essentiality annotations can be reliably transferred between both closely and distantly related species.

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Publishing Institution:IRC-Library, Information Resource Center der Jacobs University Bremen
Granting Institution:Jacobs Univ.
Author:Dawit Andualem Nigatu
Referee:Werner Henkel, Marc-Thorsten Hütt, Georgi Muskhelishvili, Hesham Ali
Advisor:Werner Henkel
Persistent Identifier (URN):urn:nbn:de:gbv:579-opus-1007989
Document Type:PhD Thesis
Language:English
Date of Successful Oral Defense:2018/03/26
Date of First Publication:2018/05/03
Academic Department:Computer Science & Electrical Engineering
PhD Degree:Electrical Engineering
Focus Area:Mobility
Call No:Thesis 2018/5

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