Biological processes, as in all physical processes, involve transfer of information. We build parallels between genomic processes and communication systems and study protein coding in terms of Shannon Theory. We provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and the amino acid (for coding DNA) level using various substitution models. Our channel capacity results on coding DNA lead to a discussion about the optimality of the natural codon-amino acid code. We provide the results of a learning algorithm searching in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity than the natural genetic code. Our results support the hypothesis of an ancient primordial code composed of 2-nucleotide codons and a later extension from a 2-nucleotide codon code to the current 3-nucleotide codon code to encode the contemporary amino acids.

 

 

Ercan E. Kuruoğlu  received MPhil and PhD degrees in information engineering from the University of Cambridge, Cambridge, United Kingdom, in 1995 and 1998, respectively.

In 1998, he joined Xerox Research Center Europe, Cambridge. He was an ERCIM fellow in 2000 with INRIA-Sophia Antipolis, France. In January 2002, he joined ISTI-CNR, Pisa, Italy. He was a visiting professor with Georgia Tech-China in 2007, 2011 and 2016, Izmir Institute of Technology in 2009, Southern University of Science and Technology of China, Shenzhen in 2017, Fraunhofer Heinrich Hertz Institute of Telecommunications in 2018 and University of Southern Australia in 2019.  He is currently a Visiting Professor at Tsinghua-Berkeley Shenzhen Institute, on leave from his Director of Research position at Institute of Science and Technology of Information-CNR (Italian National Council of Research).

He served as an Associate Editor for the IEEE Transactions on Signal Processing and IEEE Transactions on Image Processing. He is currently the editor in chief of Digital Signal Processing: A Review Journal. He acted as a Technical co-Chair for EUSIPCO 2006 and a Tutorials co-Chair of ICASSP 2014. He is a member of the IEEE Technical Committees on Signal Processing Theory and Methods and on Machine Learning for Signal Processing. He is also a member of Special Area Teams of EURASIP on Biomedical Signal and Image Analytics and on Machine Learning for Signal and Data Analytics . He was a plenary speaker at DAC 2007, ISSPA 2010, IEEE SIU 2017, Entropy 2018 and WODS-TBSI 2019 and tutorial speaker at IEEE ICSPCC 2012. He was an Alexander von Humboldt Experienced Research Fellow in the Max Planck Institute for Molecular Genetics in 2013-2015. His research interests are in the areas of statistical signal and image processing and information and coding theory with applications in computational biology, telecommunications, earth sciences and astrophysics.