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Mathematicians Solve Cellular Noise, a Long-standing Challenge in Biology
< (From left) Researcher Dongju Lim, Researcher Seokhwan Moon, Professor Jae Kyoung Kim (KAIST), Professor Jinsu Kim (POSTECH), Professor Byung-Kwan Cho (KAIST) >
Why does cancer sometimes recur even after successful treatment, or why do some bacteria survive despite the use of powerful antibiotics? One of the key culprits identified is "Biological Noise"—random fluctuations occurring inside cells. Even when cells share the same genes, the amount of protein varies in each, creating "outliers" that evade drug treatments and survive. Until now, scientists could only control the average values of cell populations; controlling the irregular variability of individual cells remained a long-standing challenge.
A joint research team—led by Professor Jae Kyoung Kim (Department of Mathematical Sciences, KAIST), Professor Jinsu Kim (Department of Mathematics, POSTECH), and Professor Byung-Kwan Cho (Graduate School of Engineering Biology, KAIST)—has theoretically established a "Noise Control Principle." Through mathematical modeling, they have found a way to eliminate biological noise and precisely govern cellular destiny. This achievement in securing precision control technology at the single-cell level is expected to be a new milestone in solving challenges in cancer treatment and synthetic biology.
While cells in our bodies strive to maintain homeostasis for survival, their internal environments are constantly changing. Existing genetic circuit technologies could regulate the average protein levels of a cell population but often ended up amplifying the "noise"—the variance between individual cells. The research team compared this to a "shower that fluctuates between boiling and freezing." Even if the average water temperature is set to 40°C, a normal shower is impossible if the water alternates between scalding and icy. Similarly, a small number of cells that escape control due to this "trap of the average" become the primary cause of cancer recurrence or antibiotic resistance. To solve this, the team devised a new mathematical model called the "Noise Controller (NC)."
The researchers first investigated whether they could control the variance of outputs—which differs from cell to cell—using a "dimerization reaction," where the final products of a system bind together to form pairs. In the process, they confirmed that the dimerization reaction could act as a sensor to detect fluctuations (noise) in the cellular state. However, initial attempts showed that this method alone had limits in reducing differences between cells. Consequently, they determined that a device was needed to immediately reduce substances if they were overproduced. They combined this with a "degradation-based actuation" principle, which promptly breaks down proteins when they become excessive. As a result, they theoretically implemented "Noise Robust Perfect Adaptation (Noise RPA)," which maintains a constant noise level despite external environmental changes. Through this, they succeeded in suppressing cell-to-cell deviation to a Fano factor of 1—the minimum level achievable by universal biological systems.
< Figure 1. Conceptual Diagram of Noise Controller (NC) Effects: When no control technology is used (top, gray), the average value of the cell population changes due to external stimuli. With existing control technology (middle, blue), the average value is maintained, but the deviation between individual cells (noise) remains large. In contrast, using the Noise Controller (bottom, green) maintains the average while also reducing the noise level of individual cells. >
The research team proved the model's performance by virtually applying it to the DNA repair system of E. coli. In the existing system, the amount of DNA-repairing proteins varied so greatly between cells that approximately 20% of the cells failed to repair and died. However, by applying the Noise Controller (NC) to unify protein levels across all cells, the mortality rate was slashed to 7%. The team significantly boosted cell survival rates through sophisticated mathematical principles alone. This is highly significant as it moves beyond the "average control" paradigm to realize "single-cell control," dealing with each cell with precision.
< Figure 2. Structure of the Noise Controller (NC).In the conventional control scheme (left), the final output (X2) produces one of the controller proteins (Z2), and this protein is degraded together with the other controller protein (Z1) that generates the system input (X1).In contrast, the noise controller (NC) established in this study (right) has a largely similar structure, but is characterized by the production of the controller protein (Z4) through a dimerization reaction of the final output. This protein directly degrades the system input (X1).Through this mechanism, mathematical expressions for the mean of the final output (lower left equation) and its noise (lower right equation) can be derived >
Professor Jae Kyoung Kim, who led the research, stated, "The significance lies in bringing cellular noise—which was previously dismissed as luck or coincidence in biological phenomena—into the realm of controllable factors through mathematical design." He added, "It will play a vital role in fields requiring precise cellular control, such as overcoming cancer treatment resistance and developing high-efficiency smart microorganisms." Co-corresponding author Professor Jinsu Kim of POSTECH emphasized, "This research demonstrates the power of mathematical modeling, starting from theoretical formulas of intracellular noise using reaction network theory and leading to the design of actual biological mechanisms."
< Figure 3. Actual Biological Circuit Structure of the Noise Controller (NC): A representation of the mathematical model established by the research team implemented as a genetic circuit, which is an actual biological system. The existing control technology (left) consists of a reaction where the final product produces an anti-sigma factor (RsiW), which then binds with the sigma factor (SigW) that generates the system’s input value. The Noise Controller (NC) (right) similarly utilizes the binding reaction between an anti-sigma factor (RseA) and a sigma factor (ECF); however, the primary differences are that the anti-sigma factor (RseA) is produced through the dimerization reaction of the final product , and that the anti-sigma factor (RseA) directly degrades the system’s input value >
The results of this study were published on December 24 in the international academic journal Nature Communications (IF=15.7).
2025.12.29 View 1587 -
A System Controlling Road Active Noise to Hit the Road
The research team led by Professor Youngjin Park of the Department of Mechanical Engineering has developed a road noise active noise control (RANC) system to be commercialized in partnership with Hyundai Motor Group.
On December 11, Hyundai Motor Group announced the successful development of the RANC system, which significantly reduces the road noise flowing into cars. The carmaker has completed the domestic and American patent applications for the location of sensors and the signal selection method, the core technology of RANC.
RANC is a technology for reducing road noise during driving. This system consists of an acceleration sensor, digital signal processor (the control computer to analyze sound signals), microphone, amplifier, and audio system. To make the system as simple as possible, the audio system utilizes the original audio system embedded in the car instead of a separate system.
The acceleration sensor first calculates the vibration from the road into the car. The location of the sensor is important for accurately identifying the vibration path. The research team was able to find the optimal sensor location through a number of tests.
The System Dynamics and Applied Control Laboratory of Professor Park researched ways to significantly reduce road noise with Hyundai Motor Group for four years from 1993 as a G7 national project and published the results in international journals. In 2002, the researchers published an article titled “Noise Quietens Driving” in Nature, where they announced the first success in reducing road noise in actual cars. The achievement did not lead to commercialization, however, due to the lack of auxiliary technologies at the time, digital amplifiers and DSP for cars for example, and pricing issues.
Since 2013, Professor Park’s research team has participated in one technology transfer and eight university-industry projects. Based on these efforts, the team was able to successfully develop the RANC system with domestic technology in partnership with Hyundai’s NVH Research Lab (Research Fellow, Dr. Gangdeok Lee; Ph.D. in aviation engineering, 1996), Optomech (Founder, Professor Gyeongsu Kim; Ph.D. in mechanical engineering, 1999), ARE (CEO Hyeonseok Kim; Ph.D. in mechanical engineering, 1998), WeAcom, and BurnYoung.
Professor Park’s team led the project by performing theory-based research during the commercialization stage in collaboration with Hyundai Motor Group.
For the commercialization of the RANC system, Hyundai Motor Group is planning to collaborate with the global car audio company Harman to increase the degree of completion and apply the RANC system to the GV 80, the first SUV model of the Genesis brand.
“I am very delighted as an engineer to see the research I worked on from my early days at KAIST be commercialized after 20 years,” noted Professor Park. “I am thrilled to make a contribution to such commercialization with my students in my lab.”
2019.12.27 View 18198