OUR TECHNOLOGY
Genome Entropy
In a scientific sense, entropy is defined as “the degree of unevenness of probability.”
For example, when a fair dice is rolled, the probability of getting a number is equal to 1/6.
However, if it is an unfair dice that made the 6’s side heavy with someone’s intention, the probability of getting the 1, which is on the opposite side of the 6, will be the greatest, and the probability of getting the six will be the least. This is the destruction of randomness, the creation of order, which means the intervention of intentions.
For example, when a fair dice is rolled, the probability of getting a number is equal to 1/6.
However, if it is an unfair dice that made the 6's side heavy with someone’s intention, the probability of getting the 1, which is on the opposite side of the 6, will be the greatest, and the probability of getting the six will be the least. This is the destruction of randomness, the creation of order, which means the intervention of intentions.
The information content can be calculated from each probability, as I_{X}(x) = - \log P_{X}(x).
The expected information content (or the average amount of information content) is called entropy, i.e., H(X) = - \sum_{x} P_{X}(x) \log P_{X}(x).
Entropy reaches a maximum when the probabilities are all equal and decreases as they become unequal
If the center of gravity in the dice is biased to one side, the probability distribution becomes uneven and entropy decreases.
As for a genome having n genes, the genome has 2^n transcriptional states, and it has a probability dwelling in each transcriptional state. We use von Neumann entropy, S(\rho)=-\text{tr}(\rho\ln\rho), where \rho is a density matrix of transcription states of the genome.
Its basic principle is the same as the case of the unfair dice: if the genome is mostly dwelling in some specific transcriptional states, the unevenness of probability will increase, and the entropy will decrease, which means that the genome is functioning for a particular purpose.
The genome produces mRNAs according to its transcriptional states
The information (entropy) generated by the transcriptional states is embedded in the amounts of mRNAs produced, and as the proteins are produced in the cytoplasm, it regulates the protein network. After all, as the transcriptional states of the genome operate the proteome, the cell exhibits its unique function.
If the entropy is low enough, the 2^n transcriptional states can be transferred to n types of mRNA with minimal information loss. Based on this, we can calculate the entropy of the genome from the mRNA expression data extracted from multiple samples for one type of tissue.