Algebraic approach reveals how to restore complex altered gene networks

Previously, research on the control of genes of genes was carried out on the basis of a single response stimulus of the cells. More recently, studies have been proposed to precisely analyze complex genes to identify control targets.

A KAVET research team has managed to develop a universal technology that identifies gene control targets in altered cell genes and restores. This achievement should be widely applied to new anticancer therapies such as cancer reversibility, drug development, precision medicine and reprogramming for cell therapy.

The research team of Professor Kwang-Hyun Cho of the Biography and Brain Engineering Department has developed a technology to systematically identify gene control targets which can restore the modified stimulus-response models to normal using an algebraic approach. The algebraic approach expresses genes of genes such as mathematical equations and identifies the control targets by algebraic calculations.

The research team represented the complex interactions between the genes of a cell as “logical circuit diagram” (Boolean network). Based on this, they have visualized how a cell reacts to external stimuli as “landscape card” (phenotype landscape).

By applying a mathematical method called “semi-temple product”, they developed a way to calculate quickly and with precision how the global cellular response would change if a specific gene was controlled.

However, because the key genes that determine the real cellular responses numbering in the thousands, the calculations are extremely complex. To remedy this, the research team applied a digital approximation method (Taylor approximation) to simplify the calculations. In simple terms, they have transformed a complex problem into a simpler formula while giving almost identical results.

Thanks to this, the team was able to calculate which stable state (attractor) that a cell would reach and predict how the state of the cell would change when a particular gene was controlled. Consequently, they were able to identify the control targets of the central genes which could restore abnormal cellular responses to the states most similar to normal.

Professor Cho’s team applied the control technology developed at various genes of genes and has verified that it can predict the gene control targets that restore the stimulus-response models to normal.

In particular, by applying it to the networks of cancer cells in the bladder, they have identified gene control targets capable of restoring modified responses to normal.

They also discovered gene control targets in large -scale deformed genes of immune cells that are capable of restoring normal stimulus response models. This allowed them to solve problems that previously required approximately approximate research via long computer simulations quickly and systematic.

Professor Cho said: “This study is assessed as an original basic technology for the development of the digital cellular twin model, which analyzes and controls the phenotype landscape of genes of genes that determine the destiny of cells.

“In the future, it should be widely applicable through life sciences and medicine, including new anticancer therapies thanks to the reversibility of cancer, the development of drugs, precision medicine and the reprogramming of cell therapy.”