M. S. students

Geunyeong Park (Biochemistry)

rmsdud502@kaist.ac.kr


Research Interests
As human life expectancy increases, it has become important to find ways to overcome cancer. Systems biology construct a dynamic model on a biological network and identify the cellular functions of the dynamic model. Through extensive large-scale computer simulation analysis, we can identify molecular targets that reverse cancer processes  and also carry out experimental validation of the molecular targets. Ultimately, my research goal is not to simply remove cancer cells, but to find reverse control targets that returns them to their normal state through the systems biology approach. 


Keywords
Reverse control, Systems biology, Cancer biology

Kyubin Park (Biological Sciences)

parkk1@kaist.ac.kr

Research Interests
There have been several studies on cancer and aging. However, such diseases could not be resolved because of the complexity arising from numerous regulating relations and components. I believe computing biological phenomena in a systemic manner can dissolve the complexity and offer new insights. My research goal is to construct a computational model for cancer or aging and demonstrate a network-based treatment strategy. And eventually suggest insights for solving diseases we thought inevitable.


Keywords

Systems biology, Network control, Bioinformatics




Hyunsoo Yeo (Bio and Brain Engineering)

nky0309@kaist.ac.kr





Research Interests
By analyzing large-scale datasets and using network control theory, we can identify key nodes and signaling pathways as targets that are crucial for reversion cancer cell to normal cell. Ultimate goal is to develop novel therapeutic strategies that targets, thereby restoring normal cellular behavior and inhibiting cancer progression. I believe we can make significant strides towards developing more effective cancer treatments and improving patient outcomes.

Keywords
Cancer biology, Network control, Systems biology

Insoo Jung (Bio and Brain Engineering)

tothetop@kaist.ac.kr

Research Interests
One of the goals of science is treating irreversible biological phenomenon such as cancer and aging. Among many treatments, reversion of these processes is novel method. To research about the reversion of irreversible biological phenomenon, we should figure out relationships between biological components. I think that the usage of Boolean network make us to handle a lot of informations comfortably. Based on control theories of Boolean network, I want to find targets for realistic biological reversion of irreversible biological process.

Keywords
Reversion, Boolean network, Control theory

Myoungbo Kang (Biotechnology & Statistic)

mbkang@kaist.ac.kr

Research Interests
I aim to conduct integrated research, spanning biology to computer modeling and simulations. While traditional cancer treatments mainly involve chemotherapy or surgery, there's a growing expectation that addressing the complexity of gene regulatory networks could lead to a more foundational and reversible approach to cancer treatment. My goal is to extract insights from extensive datasets, understand biological networks, and experimentally validate these findings, contributing to innovative and effective cancer therapeutic strategies.

Keywords
Cancer biology, Reverse control, Systems biology

Yoonsu Na (Biology & Convergence Software)

ysna99@kaist.ac.kr

Research Interests
As human health and cancer treatment is becoming one of the most important issue among the world, I think Systems Biology is a key breakthrough to deal with these issues. By modeling and analyzing various biological networks, we might be able to find novel target which is engaged in reversion of tumor to normal state. With concepts of Boolean network and control theory, I think it is not impossible to make a therapeutic strategies for unconquered cancer types.

Keywords
Network modeling, Network control, Cancer Biology

Jian Oh (Life Science & Bioinformatics)

skyhigh985@kaist.ac.kr

Research Interests
My overall goal is contribution to society through reversion of abnormal cell state to normal cell state, and further making incurable disease curable. To achieve this goal, I’m modeling complex biological networks and exploring various regulatory mechanisms that can control cell fate. Also, I am exploring more effective disease networks and treatment mechanisms by applying computational approach to vast amounts of biological and medical data.

Keywords
Cell fate control, Systems Biology, Neural Network

Ferio Brahmana (Engineering Physics)

feriobrahmana@kaist.ac.kr

Research Interests
My research interest lies in comprehending biological systems, particularly human cells, as complex dynamical entities. By conceptualizing these systems as dynamical systems, I aim to establish computable mathematical models that deepen our understanding of the intricate dynamics governing human cells. The overarching goal is to leverage this understanding to exercise control over human cell systems through computer simulation and a systems biology approach. With precise control mechanisms, there is significant potential to navigate the complex interplay of multi-interactions within human cells. I believe this approach holds promise for addressing and combating complex diseases, such as cancer, aging, and immune-related disorders, offering an intriguing perspective like the reverse control theory in the context of fighting diseases like cancer or aging.

Keywords
System Biology, Network Control, Reverse Control Theory