http://www.phy.ncu.edu.tw/~ibp/

Graduate Institute of BioPhysics at NCU
國立中央大學 生物物理所
Inst. Systems Biology & Bioinformatics
系統 生 物與生物資訊所
Life Science
生命科學系
Institute of Phys.,
Academia Sinica
中研院物理所
Brain Research Center,UST
聯合大學腦科學中心
Soft Condensed
Matter
Center for Complex Systems
複雜系統中心

What is Biophysics?
Biophysical Society defines as: "that branch of knowledge that applies the principles of physics and chemistry and the methods of mathematical analysis and computer modeling to understand how the mechanisms of biological systems work ” .
• Material Nature of Bio-substances affect
Biological properties. (Evolution made use of the physical properties of bio-materials)
• Physical principles & Laws holds from microscopic level  macroscopic level
• Traditional Biology is descriptive, nonquantitative

• Physics is universal.
• Rise of molecular biology: DNA, RNA, protein are universal in all living matters
• Universality in Central Dogma:
DNA  RNA  protein  Biological functions…
• New, interesting, exciting & useful .
• Lots of unsolved important problems.
• Techniques & Methodology in physics can probe the fundamental principles in bio-systems of a wide spectrum of scales in a quantitative way.

Physics is vital in breakthrough in life sciences
• Breakthrough in physical instrument: optical microscope (Hooke, 1665), amplifier, X-ray, electron microscope, MRI, SPM, mass spectrometer,
Single molecule microscopy,….
Nobel laureates in physiology/medicine that were physicists/had physics training:
• Georg von Békésy (physical mechanism of the cochlea, 1961)
• Francis Crick (DNA, 1962)
• Alan Hodgkin (nerve cell ,1963)
• Haldan Hartline (visual processes in the eye, 1967)
• Max Delbrück (bacteriophage l
, 1969)
• Rosalyn Yalow (radio-immunoassays of peptide hormones, 1977)
• Werner Arber (restriction enzymes , 1978)
• Erwin Neher (single ion channels in cells ,1991)
• Peter Mansfield (NMR, 2003)……

• Length Scales: nm  m m  mm  cm  m 
DNA,RNA,protein, intracellular, virus, bacteria, Intercellular, collective motion, insects, animals/plants, migration km
• Time Scales: fs  ps  m s  ms  s e transfer,H-bonding,water DNA,RNA,protein rearrangement , protein folding DNA transcription
 hr  day  year  Byr cell division Earth organisms , animal migration evolution
• Knowledge: Interdisciplinary 跨越各學科領域
Mathematics  Physics  Chemistry  Biology  Medical
• Biophysicist is a TRUE Scientist ! Explore to the maximum freedom for doing science!
•需要物理與 非物理 背景人材加入!

• Officially established in 2004( 碩士班),博士班 (2008 )
• 教授: 6 副教授: 1 助理教授 2
• 合聘教授: 3 合聘助理教授: 2
• 現有從事生物物理領域在學研究生(含物理所)
碩士班：23 博士班：7
•
• 博士後: 6
以物理之技術或方法去探討生物系統中存在之基本原
理，從而對生物過程提供深入及定量之了解。
• 「5年500億發展國際一流大學及頂尖研究中心計畫」
經費建立 生物物理共用核心設施
• 歡迎物理與 非物理 背景同學加入.中大及中研院提供獎
學金

師 資
伊 林
陳 方 玉
黎 璧 賢
王 敏 生
高 仲 明
陳 培 亮
陳 宣 毅
薛 雅 薇
李 紀 倫
李 弘 謙
陳 志 強
梁 鈞 泰
林 耿 慧
阮 文 滔
職 稱
教 授
教 授
教 授
教 授
教 授
教 授
副教授
助理教授
助理教授
合聘教授 ( 中大系生所 )
合聘教授 ( 中研院物理所 )
合聘教授 ( 中研院物理所 )
合聘助理教授 ( 中研院物理所 )
合聘助理教授 ( 中研院物理所 )
Ph.D
Rutgers University
研究專長 Email Address
複雜系統 / 生物物理 ( 實驗 ) lini@phy.ncu.edu.tw
Rice University
生物物理 / 生物膜 ( 實驗 ) fychen@phy.ncu.edu.tw
U of Pittsburgh
生物物理 / 軟凝態物理 / 神經元網路 / 生物材料
( 理論 / 實驗 ) pylai@phy.ncu.edu.tw
U of Pittsburgh
腦科學 ( 理論 ) mswang@phy.ncu.edu.tw
U of Arizona
演化的模擬 ( 理論 )
Caltech
生物圖案形成 / 軟物質 / 生物力學 ( 理論 / 實驗 )
U of Pittsburgh
軟凝態物理 / 生物物理 ( 理論 )
U of Toronto
SUNY Stony Brook
McGill University
生物膜物理 / 核磁共振 ( 實驗 )
軟凝態物理 / 生物物理 ( 理論 )
計算生物 / 生物物理 / 生物訊息 ( 理論 )
U of Pittsburgh
軟物質 / 生物物理 / 神經元網路 ( 實驗 )
UC Santa Barbara
統計物理與軟物質 / 生物集體行為 ( 理論 )
U of Pennsylvania
軟物質 / 生物材料 ( 實驗 )
National Central U
生物高分子 / 生物物理 ( 實驗 ) cmko@phy.ncu.edu.tw
peilong@phy.ncu.edu.tw
hschen@phy.ncu.edu.tw
yhsueh@phy.ncu.edu.tw
chilun@kali.pse.umass.edu
hclee@sansan.phy.ncu.edu.tw
phckchan@ccvax.sinica.edu.tw
leungkt@phys.sinica.edu.tw
khlin@phys.sinica.edu.tw
wtjuan@phys.sinica.edu.tw

BioPhysics Theory Groups at NCU
Soft matters
Biophysics
• 陳培亮 Peilong Chen: bio-hydrodynamics, mechanics of propulsion in living organisms, pattern formation in biology
• 陳宣毅 Hsuen-Yi Chen: complex fluids, cell adhesion, collective motion in flocks
• 黎璧賢 Pik-Yin Lai: DNA physics, biomolecular chain models, neurons, biological networks
• 李紀倫 Chi-Lun Lee: protein folding, charged biomolecules
• 梁鈞泰 Kwan-tai Leung: self-propelling motion in organisms, flocking, non-equilibrium bio-processes
• 高仲明 Chung-ming Ko: Evolution models, astrobiology
• 王敏生 Min-Sheng Wang: Neural Networks, brain wave &
MEG analysis
• 李弘謙 Hoong-Chien Lee: Bioinformatics, protein physics, genome/DNA sequence analysis

• Bio-Soft Core Facilities Lab.
: BioAFM, Confocal microscopy, Wet
Labs, Bio samples, fast imaging systems, fluorescence microscopy, rheometer…
• Complex System Lab.
伊林 Lin I: micro-motion of bio- and soft materials in confined spots, dynamics of neuronal system, laser pulse-soft matter interaction
• Biophysics Lab.
陳方玉 Fang Yu Chen: Biomembrane, Membrane-active
Peptides, Effect of peptide-forming pore on neuron function
• Bio-membrane Lab.
薛雅薇 Ya-Wei Hsueh: lipid rafts in cell membranes, NMR spectroscopy, AFM measurement
• Bio-Soft Matters Lab.
黎璧賢 Pik-Yin Lai , 陳志強 C.K. Chan: interactions in cells, neuronal networks, DNA mechanics & hydrodynamics, biomaterials
• Soft-condensed Matter Lab.
陳培亮 Peilong Chen : bio-hydrodynamics, mechanics of propulsion in living organisms
• Soft-Matter Lab. 林耿慧 K.H.Lin, 阮文滔 W.T.Juan: bio-soft materials, colloids, single-molecule DNA

E

Biophysics/Soft-matter
Theory & Experimental Group
Bio-Soft Matters Lab. & Simulational Physics Lab.
Principal Investigators: Pik-Yin Lai , C.K. Chan
Graduate Institute of BioPhysics & Center for Complex Systems, NCU
Bio Soft Matters Lab. Recent experimental research topics include single-molecule experiments on biomolecules
、 complex network of neuron/cardiac cells
、 synchronized firing of neuronal networks
、 dynamical/collective behavior of cells
、
DNA under flow
、 molecular motors
、 ion-channels. Drag reduction 。

Biophysics/Soft-matter
Bio-Soft Matters Lab. & Simulational Physics Lab.
Principal Investigators: Pik-Yin Lai , C.K. Chan
Graduate Institute of BioPhysics & Center for Complex Systems, NCU
Simulational Physics Lab. Simulations & analytical studies in close connection with expts. in Bio-Soft Matters Lab.
Biological networks
、 structure & dynamics of biomolecules
、
DNA elasticity/hydrodynamics 、 physics & topological interactions in knots 、 phase transitions in polymeric systems
、 grafted polymer layers
、 polymer adsorption
、 charged polymers
。

• DNA stretching, elasticity
• DNA drag reduction
• DNA thermo-phoresis
• DNA condensation
• DNA under external fields
• DNA jamming
• DNA fibers
• ………

B-form to S-form Transition under a Stretching force
Lai & Zhou, J. Chem. Physics 118, 11189 (2003)
Force Experiments
Stretching a single end-grafted DNA
S-form
B-form
•
Abrupt increase of 1.7 times in contour length of dsDNA near
65pN.
• Thermal fluctuations unimportant near onset of transition.

T7 DNA polymerase
•effect of template tension polymerase activity
•Pausing & arrest during polymerase
•Mechanism of polymerization kinetics
•Tune rate of DNA replication with external stresses

Classical mechanics approach
•(thermal effects can be neglected since the DNA is quite straight near the onset of B

S)
•All lengths in units of R, energy in units of k
/R f= f z, dimensionless force b 2
=fR /2 k , t =(sin q cos f
,sin q
,sin f
,cos q
)
Minimizing Ebs: Euler Lagrange eqns.
B.C.s:

First order phase transition at b t
First-order elongation:Stretch by untwisting b
=0.073 b
=0.075
Untwisting upon stretching
Untwist per contour length from B

S,
D
Tw/Lo~-100 deg. /nm;
•
Almost completely unwound ~ 34deg./bp
• Torque ~ 60 pN nm

Direct observation of DNA rotation during transcription by Escherichia coli RNA polymerase
Harada et al., Nature 409 , 113 (2001)
•DNA motor : untwisting gives rise to a torque
•B  S transition provides a switch for such a motor.
G
> 5 pN nm from hydrodynamic drag estimate

Dyed DNA in micropipette channel (3 m m~30 m m)
IR laser
Soret effect in microchannel
•may be used in bio-microfluidics, DNA separation process
•Possible mechanism to achieve high DNA conc. for pre-biotic life emergence in sea

Complex competition of DNA elasticity, charge interactions, volume interactions, solvent effects…..

Good turbulent drag Reducer
Poor Drag Reducer

Molecular Jamming of DNA in Gel Electrophoresis
- -
DNA+SPD
E
DNA
0.7% agarose gel
+ + + + + + + + +

Singleλ DNA with [SPD]=20mM jamming when entering in 0.7% gel from 0.5X TBE buffer solution
E

DNA in gel under AC electric field 

• DNA are negatively charged, SPD are added to bind to DNA to form aggregate  fiber
• Understand how DNA can be packed into fibers
 biological relevant for the packing of DNA in virus and nucleus
• DNA are negatively charged, SPD are added to bind to DNA to form aggregate  fiber
• Produce DNA fibers of special mechanical, electric, bio-chemical properties. Woven to DNA sheets… Bio-materials

Expt6: DNA + SPD No PEO (1%wt, 1mM)
1Day later

Simple to Complex: emerging properties of networks: Neurons & cardiac cells
Hodgkin-Huxley Model
(1952)
Signal across synapses
Neuron Cell does not divide: number of neurons non-increasing.
Complex behavior/function determined by neurons connections/synaptic strength.
Complex neuronal Network :
•A single neuron in vertebrate cortex connects ~10000 neurons
•Mammalian brain contains > 10**10 interconnected neurons
•Signal & information convey via neuronal connections—coding
Coupled oscillator networks of Cardic cells: nonlinear dynamics, spiral waves, spatiao-temporal patterns …

Expts. On giant axon of squid: time & voltage dependent Na, K ion channels
+ leakage current
I ( t ) = I
C
( t ) + I k
( t )
I k
= g
Na m
3 h
( u
-
E
Na
) + g
K n
4 ( u
-
E
K
) + g
L
( u
-
E
L
). gating variables:
= ( u
) (1 m
) ( u
) m
= ( u
) (1 n
) ( u
) n
= ( u
) (1 h
) ( u
) h a, b: empirical functions

Experiments
Schematic procedures in preparing the sample of neuron cells from celebral cortex embryonic rats
Embryos of Wistar rats
E17~E18 breeding days http://mouse.kribb.re.kr/mou sehtml/kistwistar.htm

Growth of axon connection to form a network
Typical confocal microscope pictures of cultures used in our experiments.
Red: anti-MAP2 (neuronal marker); Green, anti-GFAP (glia marker). Black &white: phase contrast image; Merge of the three images above.

Firing of the network is monitored by the changes in intracellular
[Ca 2+] which is indicated by the fluorescence probe (Oregon
Green).
Non-synchronous Firing in early stage of growth

Synchronized Firing of Neuronal Network Culture
Spontaneous firing of the cultures are induced by reducing [Mg2+] in the Buffered salt solution
Firing  the changes in intracellular [Ca 2+] indicated by the fluorescence probe.
Synchronized Firing at later stage of growth

Phys. Rev. Lett. 93 088101 (2004)
PRE (2006)
•Critical age for SF, tc
•SF freq. grows with time f=f c +f o log(t/t c ) t c

D
• P ( D )=mean prob. that 2 neurons initially separated by D will be connected
•Characteristic coupling length
• D c ~ 0.33mm ~ 2 r c

• Active growth in early stage, retarded once goal is achieved.
• Slowing down to maintain a long time span for function: homeostasis
• Continuing fast growth used up energy
• Too much connections may exceed information capacity for a single neuron

Glia and neuron mixed culture (8DIV, 5X10 5 )
0 mV
-60
Inter-burst synchronized , but intra-burst is NOT synchronized
2 s

• Continuous firing (over excited) is harmful-excitotoxicity
• Inhibitors (Glia) suppress over-excited neurons
• g=inhibitory field
• Mean-field model
• z=mean connectivity of a neuron to inhibitors
FitzHugh-Nagumo model for neurons

Synchronized Bursting Intra-burst NOT synchronized

Experimental/Theoretical students Wanted
• Experiments & Theories on bio-molecules, cells, neuronal/Cardiac physics, biological networks, biocomplex systems.
• Non-physics background are welcome!
• Interface bio/living system/molecules with materials.
• Training on nano-bio-techniques
Please contact 黎璧賢 : pylai@phy.ncu.edu.tw

Complex system Lab. 伊林 Lin I
Bio/soft matter systems :
• Micro-motion of bio- and soft materials in confined spots
• dynamics of neuronal system
• laser pulse-soft/bio matter interaction
Dusty plasma liquids:
• effects of thermal excitation, external shear, finite size confinement, etc. on the micro-structure and micro-dynamics of dusty plasma liquid at the kinetic level

Biophysics Lab.
陳方玉 Fang Yu Chen Membrane-active Peptides
(NSC project)
Anti-microbial peptides (AmP) is gene-encoded and is produced in innate immune system as the first-line defender to invading microbes and bacteria.
There are three types of AmP - -helix, b -sheet and q -ring. We have successfully proved the killing mechanism of  -helix AmP - - stretching the target cell membrane to form pores on membrane, that leads the target cell to the death.
We are now focusing at killing mechanism of those b
-sheet and q
-ring AMPs.
Effect of peptide-forming pore on neuron function
(UTS project)
Gramicidin A (GA) is a small peptide, capable of forming trans-membrane ion channel which allows monovalent cations to pass. We are studying the effect of such GA channel on neuorn function.

• Physical properties of biomembranes
• Lipid-Protein interaction
• applying solid-state NMR techniques in biological systems
Important Issues

The size of lipid rafts ?

Fraction of lipid rafts in cell membranes ?

The stability of lipid rafts ?

The origin of lipid rafts in cell membranes ?
protein sphingolipid phospholipid
● protein cholesterol
Techniques:
Nuclear magnetic resonance)
Atomic force microscopy (AFM)

Fluid Dynamics & Soft Matters
Statistical Mechanics of Electrolyte Solutions Peilong Chen
Distribution of electrolytes near interface, e.g., the cell membrane
Fluid Dynamics in Soap Film
Measuring friction at air-film interface
Pattern Formation in Faraday Waves
Pattern and mean flow interaction
Block Copolymer Shear Alignment
Derive the diffusion-stress coupled dynamics

Hsuan-Yi Chen
Pattern formation: inclusions in different states dislike each other.
increasing activities

HC Lee
•Universality, Complexity & Self-Similarity in Complete
Genomes
•Molecular dynamics simulation of Protein Structure & Function

Wang, Min-Sheng ( 王敏生 )
Inverse problem of MEG (magnetoencephalography)
Objective: To develop a method to determine the locations and strengths of synchronously activated neurons in the brain from the MEG data.
Method: The brain is divided into blocks and a certain number of current dipoles are placed at the center of each block to represent the collective effect of synchronously activated neurons in that block.
Assuming that the firing strength of all the current dipoles has the same Gaussian distribution of zero mean and large width prior to the knowledge of MEG data, the entropy of the whole system is minimized with respect to this Gaussian distribution (maximum entropy) under the constraint of MEG data.

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Officially established in 2004
Professors: 6 Assoc. Prof.: 1 Assist. Prof. 3
Adj. Prof.: 2 Adj. assist.prof.: 2
Graduate students working on areas in biophysics
M.S.
：
23 Ph. D.
：
8
Postdocs: 6 aims at achieving some quantitative description of biological processes and search for the fundamental principles buried in these highly complex biological phenomena
「
5 years 500B
」 grant to support research & building of core facility labs.
Cross-disciplinary: researchers/students from physics & non-physics background