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Dive into the research topics where Jin Seob Kim is active.

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Featured researches published by Jin Seob Kim.


The International Journal of Robotics Research | 2006

Nonholonomic Modeling of Needle Steering

Robert J. Webster; Jin Seob Kim; Noah J. Cowan; Gregory S. Chirikjian; Allison M. Okamura

As a flexible needle with a bevel tip is pushed through soft tissue, the asymmetry of the tip causes the needle to bend. We propose that, by using nonholonomic kinematics, control, and path planning, an appropriately designed needle can be steered through tissue to reach a specified 3D target. Such steering capability could enhance targeting accuracy and may improve outcomes for percutaneous therapies, facilitate research on therapy effectiveness, and eventually enable new minimally invasive techniques. In this paper, we consider a first step toward active needle steering: design and experimental validation of a nonholonomic model for steering flexible needles with bevel tips. The model generalizes the standard three degree-of-freedom (DOF) nonholonomic unicycle and bicycle models to 6 DOF using Lie group theory. Model parameters are fit using experimental data, acquired via a robotic device designed for the specific purpose of inserting and steering a flexible needle. The experiments quantitatively validate the bevel-tip needle steering model, enabling future research in flexible needle path planning, control, and simulation.


international conference on robotics and automation | 2005

Diffusion-Based Motion Planning for a Nonholonomic Flexible Needle Model

Wooram Park; Jin Seob Kim; Yu Zhou; Noah J. Cowan; Allison M. Okamura; Gregory S. Chirikjian

Fine needles facilitate diagnosis and therapy because they enable minimally invasive surgical interventions. This paper formulates the problem of steering a very flexible needle through firm tissue as a nonholonomic kinematics problem, and demonstrates how planning can be accomplished using diffusion-based motion planning on the Euclidean group, SE(3). In the present formulation, the tissue is treated as isotropic and no obstacles are present. The bevel tip of the needle is treated as a nonholonomic constraint that can be viewed as a 3D extension of the standard kinematic cart or unicycle. A deterministic model is used as the starting point, and reachability criteria are established. A stochastic differential equation and its corresponding Fokker-Planck equation are derived. The Euler-Maruyama method is used to generate the ensemble of reachable states of the needle tip. Inverse kinematics methods developed previously for hyper-redundant and binary manipulators that use this probability density information are applied to generate needle tip paths that reach the desired targets.


Molecular Simulation | 2006

Conformational Analysis of Stiff Chiral Polymers with End-Constraints.

Jin Seob Kim; Gregory S. Chirikjian

We present a Lie-group-theoretic method for the kinematic and dynamic analysis of stiff chiral polymers with end constraints. The first is to determine the minimum energy conformations of stiff polymers with end constraints and the second is to perform normal mode analysis based on the determined minimum energy conformations. In this paper, we use concepts from the theory of Lie groups and principles of variational calculus to model such polymers as inextensible or extensible chiral elastic rods with coupling between stiffnesses. This method is general enough to include any stiffness and chirality parameters in the context of elastic filament models with the quadratic elastic potential energy function. As an application of this formulation, the analysis of DNA conformations is discussed. We demonstrate our method with examples of DNA conformations in which topological properties such as writhe, twist and linking number are calculated from the results of the proposed method. Given these minimum energy conformations, we describe how to perform the normal mode analysis. The results presented here build both on recent experimental work in which DNA mechanical properties have been measured and theoretical work in which the mechanics of non-chiral elastic rods has been studied.


Biophysical Journal | 2010

Modeling the Self-Organization Property of Keratin Intermediate Filaments

Jin Seob Kim; Chang Hun Lee; Pierre A. Coulombe

Keratin intermediate filaments (IFs) fulfill an important function of structural support in epithelial cells. The necessary mechanical attributes require that IFs be organized into a crosslinked network and accordingly, keratin IFs are typically organized into large bundles in surface epithelia. For IFs comprised of keratins 5 and 14 (K5, K14), found in basal keratinocytes of epidermis, bundling can be self-driven through interactions between K14s carboxy-terminal tail domain and two regions in the central α-helical rod domain of K5. Here, we exploit theoretical principles and computational modeling to investigate how such cis-acting determinants best promote IF crosslinking. We develop a simple model where keratin IFs are treated as rigid rods to apply Brownian dynamics simulation. Our findings suggest that long-range interactions between IFs are required to initiate the formation of bundlelike configurations, while tail domain-mediated binding events act to stabilize them. Our model explains the differences observed in the mechanical properties of wild-type versus disease-causing, defective IF networks. This effort extends the notion that the structural support function of keratin IFs necessitates a combination of intrinsic and extrinsic determinants, and makes specific predictions about the mechanisms involved in the formation of crosslinked keratin networks in vivo.


Biophysical Journal | 2012

Mathematical Modeling of the Impact of Actin and Keratin Filaments on Keratinocyte Cell Spreading

Jin Seob Kim; Chang Hun Lee; Baogen Y. Su; Pierre A. Coulombe

Keratin intermediate filaments (IFs) form cross-linked arrays to fulfill their structural support function in epithelial cells and tissues subjected to external stress. How the cross-linking of keratin IFs impacts the morphology and differentiation of keratinocytes in the epidermis and related surface epithelia remains an open question. Experimental measurements have established that keratinocyte spreading area is inversely correlated to the extent of keratin IF bundling in two-dimensional culture. In an effort to quantitatively explain this relationship, we developed a mathematical model in which isotropic cell spreading is considered as a first approximation. Relevant physical properties such as actin protrusion, adhesion events, and the corresponding response of lamellum formation at the cell periphery are included in this model. Through optimization with experimental data that relate time-dependent changes in keratinocyte surface area during spreading, our simulation results confirm the notion that the organization and mechanical properties of cross-linked keratin filaments affect cell spreading; in addition, our results provide details of the kinetics of this effect. These in silico findings provide further support for the notion that differentiation-related changes in the density and intracellular organization of keratin IFs affect tissue architecture in epidermis and related stratified epithelia.


Journal of Computational Biology | 2015

Computational Analysis of SAXS Data Acquisition

Hui Dong; Jin Seob Kim; Gregory S. Chirikjian

Small-angle x-ray scattering (SAXS) is an experimental biophysical method used for gaining insight into the structure of large biomolecular complexes. Under appropriate chemical conditions, the information obtained from a SAXS experiment can be equated to the pair distribution function, which is the distribution of distances between every pair of points in the complex. Here we develop a mathematical model to calculate the pair distribution function for a structure of known density, and analyze the computational complexity of these calculations. Efficient recursive computation of this forward model is an important step in solving the inverse problem of recovering the three-dimensional density of biomolecular structures from their pair distribution functions. In particular, we show that integrals of products of three spherical-Bessel functions arise naturally in this context. We then develop an algorithm for the efficient recursive computation of these integrals.


ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference | 2015

Principles of Transference in Theoretical Kinematics

Jin Seob Kim; Gregory S. Chirikjian

The concept of symmetrical parameterizations of rigid-body motions was introduced in a paper in the Yang Symposium in 2014 in the context of biomolecular docking applications. These parameters are symmetrical in the sense that they “look the same” in a motion and in its inverse. Here we examine properties of special symmetrical parameterizations of rotations and full rigid-body motions in the plane and three-dimensional space. In particular, it is shown how special kinds of motions can “pass through”, or transfer, from left to right. And conjugations of rotation or homogeneous transforms can transfer to the symmetrical parameters.Copyright


bioinformatics and biomedicine | 2016

Symmetrical rigid body parameterization for biomolecular structures

Jin Seob Kim; Gregory S. Chirikjian

Assessing preferred relative rigid-body position and orientation is important in the description of biomolecular structures (such as proteins) and their interactions. For that purpose, techniques from the kinematics community are often used. In this paper, we review parameterization methods that are widely used to describe relative rigid body motions (in particular, orientations). Then we present the extended and updated review of a ‘symmetrical parameterization’ which was newly introduced in the kinematics community. This parameterization is useful in describing the relative biomolecular rigid body motions, where the parameters are symmetrical in the sense that the subunits of a complex biomolecular structure are described in the same way for the corresponding motion and its inverse. The properties of this new parameterization, singularity analysis and inverse kinematics, are also investigated in more detail. Finally the parameterization is applied to real biomolecular structures to show the efficacy of the symmetrical parameterization in the field of computational structural biology.


Robotica | 2016

Inverse kinematic solutions of 6-D.O.F. biopolymer segments

Jin Seob Kim; Gregory S. Chirikjian

Robotica / Volume 34 / Issue 08 / August 2016, pp 1734 1753 DOI: 10.1017/S0263574716000138, Published online: 13 April 2016 Link to this article: http://journals.cambridge.org/abstract_S0263574716000138 How to cite this article: Jin Seob Kim and Gregory S. Chirikjian (2016). Inverse kinematic solutions of 6-D.O.F. biopolymer segments. Robotica, 34, pp 1734-1753 doi:10.1017/S0263574716000138 Request Permissions : Click here


bioinformatics and biomedicine | 2015

Cross-validation of data in SAXS and cryo-EM

Bijan Afsari; Jin Seob Kim; Gregory S. Chirikjian

Cryo-Electron Microscopy (EM) and Small Angle X-ray Scattering (SAXS) are two different data acquisition modalities often used to glean information about the structure of large biomolecular complexes in their native states. A SAXS experiment is generally considered fast and easy but unveiling the structure at very low resolution, whereas a cryo-EM experiment needs more extensive preparation and post-acquisition computation to yield a 3D density map at higher resolution. In certain applications, one may need to verify if the data acquired in the SAXS and cryo-EM experiments correspond to the same structure (e.g., prior to reconstructing the 3D density map in EM). In this paper, a simple and fast method is proposed to verify the compatibility of the SAXS and EM experiments. The method is based on averaging the 2D correlation of EM images and the Abel transform of the SAXS data. The results are verified on simulations of conformational states of large biomolecular complexes.

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Bijan Afsari

Johns Hopkins University

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Chang Hun Lee

Johns Hopkins University

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Noah J. Cowan

Johns Hopkins University

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Sean X. Sun

Johns Hopkins University

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Baogen Y. Su

Johns Hopkins University

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Sipu Ruan

Johns Hopkins University

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Yu Zhou

Johns Hopkins University

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