Yonsei University · 情報科学
Professor Sanghyun Park's research spans computational biology, systems biology, and bioinformatics, with a focus on understanding molecular signaling mechanisms, particularly through scaffold proteins in cellular signaling pathways. His lab develops advanced computational methods for sequence analysis, molecular dynamics simulations, and reaction pathway modeling to uncover the kinetic and structural principles underlying biological processes such as excitation transfer in photosynthesis. The lab also applies systems-level approaches to public health data, integrating personal, social, and environmental factors to study physical activity behaviors. Additionally, they innovate in drug repositioning by leveraging protein localization and network propagation to improve prediction of drug-disease associations.
Figures are computed from collected data and may differ slightly.
How scaffold proteins control information flow in signaling pathways is poorly understood: Do they simply tether components, or do they precisely orient and activate them? We found that the yeast mitogen-activated protein (MAP) kinase scaffold Ste5 is tolerant to major stereochemical perturbations; heterologous protein interactions could functionally replace native kinase recruitment interactions, indicating that simple tethering is largely sufficient for scaffold-mediated signaling. Moreover, b
Article Share on Segment-based approach for subsequence searches in sequence databases Authors: Sanghyun Park Department of Computer Science, University of California, Los, Angeles, Los Angeles, CA Department of Computer Science, University of California, Los, Angeles, Los Angeles, CAView Profile , Sang-Wook Kim Department of Computer, Information, and Communications Engineering, Kangwon National University, Korea Department of Computer, Information, and Communications Engineering, Kangwon Natio
Simulated tempering is a method to enhance simulations of complex systems by periodically raising and lowering the temperature. Despite its advantages, simulated tempering has been overshadowed by its parallel counterpart, replica exchange (also known as parallel tempering), due to the difficulty of weight determination in simulated tempering. Here we propose a simple and fast method to obtain near-optimal weights for simulated tempering, and demonstrate its effectiveness in a molecular dynamics
Finding representative reaction pathways is important for understanding the mechanism of molecular processes. We propose a new approach for constructing reaction paths based on mean first-passage times. This approach incorporates information about all possible reaction events as well as the effect of temperature. As an application of this method, we study representative pathways of excitation migration in a photosynthetic light-harvesting complex, photosystem I. The paths thus computed provide a
In the social ecological model, personal characteristics are important determinants of health behaviors, however, multi-dimensional approaches that consider social and physical environments must be utilized to gain a broader picture. Accordingly, this study examines the effects of personal, social, and physical environment variables as factors affecting levels of physical activity (METs). Our findings are based on 72,916 responses from the 2015 Community Health Survey in South Korea. Individual
Identifying alternative indications for known drugs is important for the pharmaceutical industry. Many computational methods have been proposed for predicting unknown associations between drugs and target proteins associated with diseases. To produce better prediction, researchers should not only develop accurate algorithms but identify good features that reflect intracellular systems. In this paper, we proposed a novel method for exploiting protein localization. We generated localization vector
Markov state models are kinetic models built from the dynamics of molecular simulation trajectories by grouping similar configurations into states and examining the transition probabilities between states. Here we present a procedure for validating the underlying Markov assumption in Markov state models based on information theory using Shannon's entropy. This entropy method is applied to a simple system and is compared with the previous eigenvalue method. The entropy method also provides a way
The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely availabl
In the future network with Internet of Things (IoT), each of the things communicates with the others and acquires information by itself. In distributed networks for IoT, the energy efficiency of the nodes is a key factor in the network performance. In this paper, we propose energy-efficient probabilistic routing (EEPR) algorithm, which controls the transmission of the routing request packets stochastically in order to increase the network lifetime and decrease the packet loss under the flooding
Open papers in the app to read, cite, and organize with AI.
