Conference Program of WCICA 2012

Conference Program WCICA 2012
epidemic and leads to a new population relation. Moreover, the effectiveness
of a simple epidemic control strategy on a weighted adaptive
network is examined. The results show that the weight adaption process
may reduce the strategy efficiency. Analysis are presented and
the results support our numerical simulations.
◮ SaB08-4 16:50–17:10
Identification of overlapping communities in protein interaction networks
using multi-scale local information expansion, pp.5071–5076
Li, Huijia
Liu, Zhi-Ping
Chen, Luonan
Zhang, Xiang-Sun
Chinese Acad. of Sci.
Chinese Acad. of Sci.
Chinese Acad. of Sci.
Chinese Acad. of Sci.
Most existing clustering approaches require the complete graph information,
which is often impractical for large-scale protein-protein interaction
networks. We proposed a novel algorithm which does not embrace
the universal approach but instead tries to focus on local ties and model
multi-scales of biological interactions in these networks. It identifies
functional leaders and modules around these leaders using local information.
It naturally supports overlapping information by associating
each node with a membership vector that describes its involvement of
each community. In addition to uncover overlapping communities, we
can describe different multi-scale partitions allowing to tune the characteristic
size of biologically meaningful modules. The high efficiency and
accuracy of the proposed algorithm make it feasible to be used for accurately
detecting community structure in real biomolecular networks.
◮ SaB08-5 17:10–17:30
Colored Petri Nets to Model Gene Mutation Classification, pp.5077–
5082
Yang, Jinliang
Gao, Rui
Meng, Max, Q.-H.
Tarn, Tzyh-Jong
Shandong Univ.
Shandong Univ.
The Chinese Univ. of Hong Kong
Washington Univ., St. Louis, MO
The genetic code is the triplet code based on the three-letter codons.
Choosing a feasible model for processing these codons is a useful
method to study genetic processes in molecular biology. As an effective
model of discrete event dynamic systems (DEDS), Colored Petri Net
(CPN) has been used for modeling several biological systems. According
to the genetic code table, CPN is employed to model the process
of genetic information transmission. In this paper, we propose a CPN
model to classify the type of gene mutations via contrasting the bases
of DNA strands and the codons of amino acids along the polypeptide
chain. This model is helpful in determining whether a certain gene mutation
will cause the changes of the structures and functions of protein
molecules. The effectiveness and accuracy of the presented model are
illustrated by the examples in this paper.
◮ SaB08-6 17:30–17:50
Core Module Network Construction for Breast Cancer Metastasis,
pp.5083–5089
Yang, Ruoting
Daigle, Bernie
Petzold, Linda
Doyle, Francis
UNIV OF CA @ SANTA BARBARA
Univ. of California Santa Barbara
Univ. of California Santa Barbara
Univ. of California Santa Barbara
For prognostic and diagnostic purposes, it is crucial to be able to separate
the group of ”driver” genes and their first-degree neighbours,
(i.e. ”core module”) from the general ”disease module”. To facilitate
this task, we developed a novel computational framework COMBINER:
COre Module Biomarker Identification with Network ExploRation. We
applied COMBINER to three benchmark breast cancer datasets for i-
dentifying prognostic biomarkers. We generated a list of ”driver genes”
by finding the common core modules between two sets of COMBINER
markers identified with different module inference protocols. Overlaying
the markers on the map of ”the hallmarks of cancer” and constructing
a weighted regulatory network with sensitivity analysis, we validated
29 driver genes. Our results show the COMBINER framework to be
a promising approach for identifying and characterizing core modules
and driver genes of many complex diseases.
◮ SaB08-7 17:50–18:10
Closed-Loop Blood Glucose Control Using Dual Subcutaneous Infusion
of Insulin and Glucagon Based on Switching PID Controller, pp.5023–
5029
Gao, Xiaoteng
Wang, Youqing
Beijing Univ. of Chemical Tech.
Beijing Univ. of Chemical Tech.
Glucose management is an important clinical task for diabetic patients,
and intensive insulin therapy is widely considered a promising way for
the glucose management. However, the intensive insulin therapy has
one potential risk: hypoglycemia, but there is no antagonist to compensate
hypoglycaemia in the intensive insulin therapy. Dual infusion of
insulin and glucagon can overcome this shortcoming. In this paper, a
switching control algorithm was proposed to design and optimize the
insulin and glucagon infusion rates simultaneously, and this algorithm
has been implemented in a virtual type 1 diabetic subject. The in silico
results demonstrate that the proposed algorithm can reduce hypoglycaemia
significantly.
◮ SaB08-8 18:10–18:30
Study on Some Modeling Problems in the process of Gene Expression
with Finite State Machine, pp.5066–5070
Gao, Rui
Shandong Univ.
Finite state machine (FSM) theory has great potentialities in understanding
key concepts and analyzing molecular biological systems, e-
specially in the process of gene expression. Based on the previous
research work, this paper extends the study on the control problems in
metabolism and gene mutation with FSM. The goal is to interpret how
to apply control technologies to process of metabolism, and how to e-
liminate the effects to secondary structures of protein caused by gene
mutation. We hope the proposed model-based analysis will provide an
exploration of new interdisciplinary theories intersected by information
science, control theory, and the Molecular Biology.
SaB09 15:50–17:50 Room 311A
Award: Application (II)
Chair: Duan, Guang-Ren
Co-Chair: Yang, Chunhua
Harbin Inst. of Tech.
Central South Univ., China
◮ SaB09-1 15:50–16:10
Error Modeling and Analysis in Dynamic Wafer Handling, pp.3977–
3982
Cheng, Hongtai
Chen, Heping
Mooring, Ben
Stern, Harold
Texas State Univ.
Texas State Univ.
Lam Research Corporation
Texas State Univ.
Wafer handling robots are used to transfer wafers in semiconductor
manufacturing. Typically a pick-measure-place method is used to transfer
wafers accurately between stations. The measurement step is performed
using an aligner, which is time-consuming. To increase the
wafer transfer efficiency, it is desirable to speed up the measurement
process or place it in parallel with other operations. Hence optic sensors
are installed at each station to estimate the wafer eccentricity onthe-fly.
The estimate process is mainly consist of two stages: sensor
calibration and wafer eccentricity estimation. Theoretical analysis and
numerical optimization methods are used to accomplish these tasks.
Based on the wafer handling robot kinematics model, robot kinematics
error, sensor calibration error and eccentricity identification error are
analyzed in this paper. The effect of data sampling methods are also
discussed. The proposed methods are validated using a wafer handling
robot system. Experiment results demonstrate that the error analysis
methods can greatly reduce the wafer eccentricity estimation error
on-the-fly. Hence the developed methods can be used to improve the
wafer handling accuracy and reduce the wafer handling cycle time in
semiconductor manufacturing.
◮ SaB09-2 16:10–16:30
Planning Expected-time Optimal Paths for Target Search by Robot,
pp.3881–3886
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