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Program
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FRIDAY 16 October 2009
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17:00 - 20:00
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City
tour and drinks at Leisure City International Hotel
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SATURDAY 17 October 2009
Master of ceremonies: Prof. Fuqing Yang
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8:30 - 9:15
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Registration
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9:15 - 9:30
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Opening
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Invited
presentation
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9:30 - 10:30
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Molecules as Automata
Luca Cardelli
Substantially Causative Factor Discovery for SNP Association
Study based on Association Stability
Junying (Joanna) Zhang
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10:30 - 10:40
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Morning
tea
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10:40 - 11:40
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DNA as a versatile programming language for
nano-engineering
Fumiaki Tanaka
Microelectronics-Embedded Channel Bridging
and Signal Regeneration of Injured Spinal Cords or among Neuron Assemble
Prof. Zhi-Gong Wang
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Oral
presentations
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Session 1(DNA Computing)
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Session chair: Prof Cui Guangzhao
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13:30-14:00
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A DNA-based supercomputing for privilege query in
hybrid role hierarchy
Guan Rong
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14:05- 14:35
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Deterministic Algorithm for the Reordering Problem
Using Tile Assembly
Yufang Huang
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14:40 - 15:00
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Afternoon tea
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15:00 - 15:30
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Implementation of the 0-1 Multi-objective Knapsack Problem
Using Self-assembly of DNA Tiles
Zhen Cheng
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15:35 - 16:05
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A
molecular computing model for 3-coloring graph problem based on circular
DNA branch migration
Zhang
Cheng
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16:10 - 16:40
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Bio-inspired Self-Organization for Supporting
Dynamic Reconfiguration of Modular Agents
Kiwon
Yeom
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16:40 - 17:40
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Student colloquium
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Session 2(Evolutionary Computing)
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Session chair: Prof Gao Lin and Prof Huo Hongwei
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13:30 - 14:00
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A Hybrid Evolutionary Algorithm for
Multiobjective Optimization
Chang Wook Ahn
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14:05 - 14:35
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A Novel Cooperative Bacterial Foraging
Algorithm
Yichuan Shao
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14:40 - 15:00
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Afternoon tea
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15:00 - 15:30
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Combining Genetic Algorithms with Optimality
Criteria Method for Topology Optimization
Zhimin Chen
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15:35 - 16:05
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An Exploratory Study of Sorting Particle
Swarm Optimizer for Multiobjective Optimization
ZHENG Bing
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16:10 - 16:40
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Multi-Criteria Evaluation Model
Reveals SMC4L1 Gene Maybe a Breast Cancer Susceptibility Gene
Chao Xu
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16:40 - 17:40
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Student colloquium
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Session 3(Membrane Computing and
others)
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Session chair: Prof Linqiang Pan
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13:30 - 14:00
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A Quantum-Inspired Evolutionary Algorithm Based on
P systems for Radar Emitter Signals
Chunxiu Liu
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14:05 - 14:35
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Solving Satisfiability Problems with Membrane
Algorithms
Gexiang Zhang
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14:40 - 15:00
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Afternoon tea
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15:00 - 15:30
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Solving 3-Coloring Problem by Tissue P Systems
with Cell Separation
Shuo Wang
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15:35 - 16:05
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Obtaining Homology Groups in Binary 2D Images Using
P Systems
Hepzibah A. Christinal
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16:10 - 17:10
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Student colloquium
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Sunday, 18 October 2009
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Regular presentation
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8:30 – 9:30
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Poster:
DNA Algorithm on Making Spanning Tree Problem
Kang Zhou
DNA computing-based cryptography
Xing Wang
A Multilevel Image Encryption Algorithm Based on
Chaos and DNA Coding
Qian Wang
An Image Encryption Algorithm Based on DNA Sequence
Addition Operation
Qiang Zhang
Molecular Beacon-based DNA computing model for
Maximum weight clique problem
zhixiang Yin
Programming Problem Based on Sticker Model
Lingying Zhi
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9:35-9:55
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Overview and Study focuses of microfluidic-based
cell culture systems
Manguo Huang
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10:00 - 10:20
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Three chains of DNA calculate for a category of
special integer planning problem
Sheng song Bo
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10:20 – 10:40
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Morning tea
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Session 1
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Session chair: Dr. Luca Cardelli, Prof
Yin Zhixiang
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10:50 - 11:20
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Three chains of DNA calculate for a category of
special integer planning problem
Bosheng Song
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11:25 - 11:55
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DNA Algorithm on Optimal Path Selection for Bus
Travel Network
Qian Zhang
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12:00 - 12:30
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Evolutionary Optimization Programming with
Probabilistic Models
Moongu Jeon
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12:30 - 13:30
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Lunch
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13:30 - 14:30
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Poster:
Molecular Beacon Based DNA Computing Model for 0-1
Programming Problem
Xiaohui Huang
A position-slots model for nucleosome assembly in
the yeast genome based on integrated multi-platform
Jihua Feng
Molecular Computations of the Maximal Clique
Problem Using DNA Self-assembly
Jing Yang
Efficient DNA Algorithm for Constructing Ramsey
Graph based on Minimal Degree Vertex
Fang Xi
Development of an in vivo computer for 3-SAT
Problem
Xiangrong Liu
DNA Computation Model Based on Self-Assembled
Nanoparticle Probes for 0-1 Integer Programming Problem
Fei Li
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14:30 - 14:50
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On the lower bounds of DNA word sets for DNA
computing
Bin Wang
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14:50 - 15:10
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The Research of Codeword Problem in DNA Computing
Hu Juan
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15:10 - 15:30
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Afternoon tea
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15:35 - 15:55
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Overview and Study focuses of microfluidic-based
cell culture systems
Manguo Huang
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16:30 - 17:30
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DNA Codewords Design Using the Improved
Non-dominated Sorting Genetic Algorithm-II
Yanfeng Wang
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17:30 till late
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Sunset drinks and
conference dinner
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Session 2(Evolutionary Computing)
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Session chair: Qiang Zhang
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8:30– 9:30
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Poster:
Classification of 31P MRS for Liver Cancer in vivo
Jun Sang
A Comparative Study of Clustering Algorithms for
Protein Sequences
DongMing Tang
Experimental Comparisons of Clonal Selection
Algorithms with Different Metadynamics Strategies
Xingxin Pei
Dynamical Model of P53-Mdm2-P14/19ARF Network to
Radiation in Population of Cells
Hui Liu
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10:50 - 11:20
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The Novel Non-linear Strategy of Inertia Weight in
Particle Swarm Optimization
Li Li
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11:25 - 11:55
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Method of Extracting Image Geometric Primitives
Based on Immune Algorithm
ZHI Jun
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12:00 - 12:30
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A PSO-FUZZY Group Decision-making Support System
in Vehicle Performance Evaluation
Li Zhang
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12:30 - 13:30
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Lunch
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13:30 - 14:00
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Combining Genetic Algorithm and Random
Projection Strategy for (l, d)-Motif Discovery
Hongwei Huo
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14:05 - 14:35
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Theoretical and Empirical Analyses of Evolutionary
Negative Selection Algorithms for a Combinational Optimization Problem
Xingxin Pei
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14:40 – 15:00
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Afternoon tea
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15:00 - 15:30
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A Novel Approach to HMM-Based Speech Recognition System
Using Particle Swarm Optimization
Negin Najkar
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15:35 - 16:05
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Quantum Swarm Evolutionary Algorithm With
Time-Varying Acceleration Coefficients for Partner Selection in Virtual
Enterprise
Jianhua Xiao
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16:10 - 16:40
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An Effective Initialization Strategy of Pheromone
for Ant Colony Optimization
Qiguo Dai
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16:45 – 17:15
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Using the BPSO Algorithm in Image Segmentation for
Dynamic Thresholding
L.Djerou
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17:30 till late
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Sunset drinks and
conference dinner
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Session 3(Membrane Computing and
others)
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Session chair: Prof. Gexiang Zhang
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8:30– 9:30
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Poster:
Measurement and evaluation of the material
metabolism capability in typical Chinese cities
Yating Li
A study of gaits in Parkinson's patients using
Autoregressive Model
Yang Han
Prediction of Interspecies Transmission for Avian
Influenza A Virus Based on BP Neural Network
Xiaoli Qiang
Orthogonal Locality Discriminant Embedding for
Document Classification
Ziqiang Wang
Spectral Clustering for Detecting Protein
Complexes in PPI Networks
Guimin Qin
Partitioning the State Space By Critical States
Zhao Jin
Application of Rough Set and Support Vector
Machine in Competency Assessment
Huizhen Liu
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9:35-9:55
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P Systems and Context-free 2D Picture Languages
K.G. Subramanian
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10:00 - 10:20
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Pulse Coupled Neural Network Based Anisotropic
Diffusion Method for 1/f Noise Reduction
Deng Zhang
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10:20 - 10:40
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Moring Tea
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10:40 - 11:00
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Constrained Trajectory Optimization Using Migrant Particle
Swarm Optimization Algorithm
Fuqiang Xie
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11:05 - 11:25
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Generic Object Recognition with
Biologically-Inspired Features
Changxin Gao
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11:30 - 11:50
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Lunch
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11:50 - 13:30
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A Nonlinear Grade Estimation Method Based on Wavelet
Neural Network
LI Xiao-li
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13:30 - 14:30
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Prediction of Protein-Protein Interaction Types
Using the Decision Templates
Wei Chen
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14:30 - 14:50
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Afternoon tea
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14:50 - 15:10
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Output Tracking Control of Switched Nonlinear Singular
System Using Neural Networks
Xin Chen
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15:15 - 15:35
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Solving Multidimensional 0–1 Knapsack Problem by
Tissue P Systems with Cell Division
Juanjuan He
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15:40 - 16:00
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A Biologically Motivated Corner Detection Method
Based on the Oriented Receptive Fields of Simple Cortical Cells
Wanying Xu
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16:30 - 17:30
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Close
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17:30 till late
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Sunset drinks and
conference dinner
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Mon.,19 October 2009
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Optional post-conference tour
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Invited
speakers
The
invited speakers for BIC-TA 2009 and abstracts of their presentations are
given below. You can view the professional biographies of the invited
speakers by clicking on their names.
The
invited speakers for BIC-TA 2008 and abstracts of their presentations are
given below. You can view the professional biographies of the invited
speakers by clicking on their names.
Luca Cardelli (Microsoft
Research, Cambridge UK))
Title: Molecules as Automata
Abstract:
Chemical
and biochemical systems are described as collectives of interacting
stochastic automata: each automaton represents a molecule that undergoes
state transitions. This framework constitutes an artificial biochemistry,
where automata interact by the equivalent of the law of mass action. We
analyze systems and networks, both by stochastic and continuous methods,
and relate the two approaches. Interacting automata are a computational
system inspired by biochemistry, but it is also possible to go the other
way, and implement these automata by using DNA technology.
Fumiaki
Tanaka
(Tokyo University)
Title: DNA as a
versatile programming language for nano-engineering
Abstract
DNA is a bio-molecule that contains information in
its sequence.
Nowadays, we can design DNA sequences and purchase
them at a reasonably low cost.
This enables us to control the hybridization
(binding) between DNA molecules with appropriately designed sequences.
Thus, DNA is a useful material for engineering such
as nano-fabrication, nano-robotics, molecular computation, and so on.
In fact, many researchers succeeded in the
construction of various molecular systems including logic gates and
nanostructures by DNA.
In this talk, I will start with the explanation why
I regard DNA as a programming language.
Then, I introduce representative molecular systems:
DNA enzyme-free logic gates and 2D or 3D DNA nanostructures.
Through these examples, I discuss how to design and
implement these molecular systems.
Zhigong Wang(Southeast University)
Title: Microelectronics-Embedded
Channel Bridging and Signal Regeneration of Injured
Spinal Cords or among Neuron Assemble
Abstract
Due to the difficulty in the regeneration of injured
spinal cord by biological methods, microelectronic neural bridge, which is
a new concept based on microelectronic technology, is presented. The
microelectronic system has been realized in the forms of hybrid and
integrated circuits. The integrated circuits for neural signal detecting,
stimulation, and regeneration are realized in a CMOS process. In the animal
experiments with 100 toads, 48 rats, and 3 rabbits, nerve signals have been
successfully detected from spinal cords and sciatic nerves, and functional
electrical stimulation has been carried out for spinal cords and sciatic
nerves. When the microelectronic system is bridged between the controlling
and stimulated nerve, the relevant motion of legs and nerve signal
waveforms, which are stimulated by evoked or spontaneous nerve signal
through such system, have been observed. Therefore, the feasibility of the
presented method was demonstrated.
In addition, we have developed a microelectrode
array (MEA) chip for in-vitro signal stimulating. recording, and bridging
of neuron assemble. The chip comprises 14´14 active sensor
cells. Each sensor cell is 6mm´6mm in
dimension, including a 15mm´25mm
stimulating electrode, a 15mm´25mm
recording electrode, two NMOS switches which can linearly transfer signals
with peak-to-peak values from 50 mV to 500 mV. The chip is realized in a
standard 0.5 mm DPDM (double-poly double-metal) CMOS technology and will be
used as interface of a neuron assemble and an electronic system.
Junying (Joanna) Zhang (Xidian
University)
Title: Substantially
Causative Factor Discovery for SNP Association Study based on Association
Stability
Abstract:
The ultimate goal of the approach is to identify the
substantially causative relations between SNP products and phenotypes, and
hence the top priority of this approach is to develop a reverse engineering
method that provides significant predictions.
In this approach, SNP association study as a typical
biologically initiated data-driven reverse engineering problem, is divided
into two phases: substantially causative (SC) factor discovery, referred
briefly to as SC-FD, and substantially causative interaction between each
SC factor and the trait, referred to as SC model estimation, or briefly
SC-ME. The ultimate goal is to understand biological mechanism of
phenotypes on SNPs, and to even further interfere in the variants of the
SNPs biologically for treatment of disease. Both are of great challenges:
no precise definition on the problem yet, no prior knowledge, noisy data,
curse of dimensionality, and insensitivity to techniques used (since the
substantial cause of a disease does not matter with the techniques used and
absolutely classifier independent). It becomes more serious when it is a
genome-wide study on both discovering methods and computation expenses. All
makes present feature based approaches (e.g., feature selection) not
available.
In this approach, a brand new approach for the
reverse engineering SC factor discovery is proposed. At first, we make four
reasonable conjectures on the SC factors: large association (Conj 1), large
stability (Conj 2) and large joint effect (Conj 3), all for one SC factor,
and non-overlap between the SC factors (Conj 4). By the light of the
conjectures, association, stability and joint effect of a factor are
mathematically defined. In addition, discover-and-remove framework for SC
factor discovery is given, which includes three consecutive phases:
searching a factor pool, gaining candidate SC factors from the factor pool,
and selecting a SC factor from the candidate SC factors. The
computationally acceptable SC factor discovery (SC-FD) algorithm is
proposed which includes three algorithms for the three phases.
The characteristics of SC factors and feasibility of
applying and evaluating the performance of our proposed algorithm to the
analysis of large numbers of SNPs was investigated primarily via
simulation. The data comes from 223 individuals that were genotyped on the
317K Illunina HumanHap300 BeadChip, and processed by biologists to form SNP
datasets of different number of SNPs. 100SNPs dataset, 250SNPs dataset,
500SNPs dataset, 1000SNPs dataset, and 2000SNPs dataset, where the number
of SNPs is 100, 250, 500, 1000, and 2000 respectively, with 7 ground truth
factors of different sizes hidden by biologists in each dataset were used
in our experiment. By running the proposed SC-FD algorithm on each of these
datasets, 5 or even 6 out of 7 ground truth SC factors were successfully
discovered for each dataset. This indicates that the proposed algorithm is
very effective in SC factor discovery. Other real dataset experiments were
also performed.
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