|
2011年
|
| 报告题目： |
Dynamic centrality measures and
adaptation of networks in crisis |
| 报
告 人： |
Prof. Peter Csermely,Semmelweis University,
Budapest, Hungary |
| 时间地点： |
2011年9月12日上午9:00 思源楼1013 |
| 摘 要： |
Determination of centrality became
a key question of the network-description of complex systems.
Former studies highlighted the importance of local measures
(such as degree) discriminating hubs, and of global measures
(such as betwenness centrality) often identifying bridges or
bottlenecks. We recently developed a modularization method,
called ModuLand ([1], www.linkgroup.hu/moduland.php), which
detects extensively overlapping network communities, and determines
community centrality, i.e. a mesoscopic measure summing up the
total influence of all network segments to a given node or link.
Community centrality proved to be useful to identify the cores
of modules, i.e. those few nodes, which form the center of the
module. Analysis of the role of module core nodes proved to
be a very good predictor of the function of the entire module
in biological systems. Similar influence-like centralities can
be derived using our recently developed Turbine algorithm to
follow the propagation of perturbations in real world networks
(www.linkgroup.hu/Turbine.php).
Based on our earlier studies on spatial games (showing that
memory plus randomness not only promote cooperation, but also
make the outcome quite independent of the network structure)
[2], we constructed NetworGame (www.linkgroup.hu/NetworGame.php),
which is a versatile program package to model any types of two-agent
games (with 2 to 5 strategies) in any real world, or model networks
using any types of strategy update rules, update dynamics and
starting strategies. The NetworGame program allowed the definition
of game centrality as the ability of a networked agent (or a
link of two agents) with a single initial defective strategy
to change an overall initial starting cooperation to defection
(and vice versa: a cooperative strategy of a linked node-pair/triangle
changing overall defection to cooperation). Spatial games can
also be rationalized in networks of non-conscious agents, such
as amino acids, or proteins [3]. Our game centrality measures
correctly identified the major decision makers of social cooperation
in benchmark networks, such as the Zachary karate club network
or Michael's strike network, and pinpointed key 'actors' determining
the cooperation of biological networks.
As an example of general messages of the dynamic behavior of
biological systems, we observed a partial decoupling of yeast
protein-protein weighted interaction network modules after stress.
This rearrangement is beneficial to the cell, because it allows
better focusing on vital functions, thus sparing resources,
and localizes damage to only the most sensitive modules. It
also reduces the propagation of noise throughout the network,
allows the individual modules a larger degree of freedom for
exploring different adaptation strategies, and helps reduce
inter-modular conflicts during a period of major intra-modular
changes. Several key proteins of the cellular stress response
served as residual or newly induced overlaps and bridges of
the yeast interactome. De-coupling/re-coupling cycles emerged
as a general model of adaptation and learning of complex systems
[4].
References
[1] I. A. Kovács, R. Palotai, M. S. Szalay, P. Csermely, Community
landscapes: a novel, integrative approach for the determination
of overlapping network modules. PLoS ONE 7, e12528 (2010).
[2] S. Wang, M. S. Szalay, C. Zhang, P. Csermely, Learning and
innovative elements of strategy update rules expand cooperative
network topologies. PLoS ONE 3, e1917 (2008).
[3] P. Csermely, R. Palotai, R. Nussinov, Induced fit, conformational
selection and independent dynamic segments: an extended view
of binding events. Trends Biochem. Sci. 35, 539 546 (2010).
[4] A. Mihalik, P. Csermely, Heat shock partially dissociates
the overlapping modules of the yeast protein-protein interaction
network: a systems level model of adaptation. PLoS Comput. Biol.
7, e1002187 (2011) |
| |
|
| 报告题目： |
Sparse Coding: Structured Sparsity,
Models and Algorithms |
| 报
告 人： |
Chris H.Q. Ding,(丁宏强) ,University
of Texas at Arlington and 安徽大学 千人计划特聘教授 |
| 时间地点： |
2011年7月28日上午10:00 思源楼1013 |
| 摘 要： |
In sparse coding (compressed sensing),
an input signal (an image or data instance) is encoded with
a small number of dictionary signals. This leads to an improved
presentation of the input signal, comparing to traditional orthogonal
basis methods. It is soon realized that "structured sparity"
is more useful in machine learning and pattern recognition.
For example in feature selection, this enforces entire row of
the regression coefficients to be zero, thus eliminates this
feature dimension. In this talk, we will briefly explain sparse
coding methods using L1, L2,1, L0 norm based models, their applications,
and solution algorithms. These matrix-based models of pattern
recognition demonstrate the power of matrix approach.
Talk based on "Towards Structural Sparsity: An explicit
L2/L0 Approach", D. Luo, C. Ding, H. Huang, best-paper-runner-up
in ICDM 2010, and "Efficient and Robust Feature Selection
via Joint l2,1-Norm Minimization", NIPS 2010, F. Nie, H.
Huang, X. Cai, C. Ding. |
| |
|
| 报告题目： |
Computational analysis of large-scale
sequencing data |
| 报
告 人： |
Prof.Ting Chen,美国南加州大学分子计算生物学中心 |
| 时间地点： |
2010年5月27日上午10:30 思源楼1013 |
| 摘 要： |
Sequencing of DNA and cDNA libraries
on "next-generation" sequencing (NGS) platforms has
become the method of choice for genomic and transcriptional
analyses. One obstacle that inhibits wider adoption of NGS techniques
is the lack of (1) fast and efficient algorithms and mathematical
methods for large-scale data analysis, and (2) comprehensive,
yet easy to use software packages with which to conduct data
analysis. To meet this need, we have developed several analytic
tools, including PerM (short read alignment), ComB (SNP Calling),
Clippers (Indel/Junction detection), and WeaV (de novo assembly),
and a software workflow called RseqFlow for the analysis of
RNA-seq data |
| |
|
| 报告题目： |
复杂网络与运筹学 |
| 报
告 人： |
史定华 教授 上海大学理学院 |
| 时间地点： |
2011年5月26日（星期四）下午3:00-5:00 思源楼712室 |
| 摘 要： |
将介绍复杂网络与运筹学的关系。以我们团队的两个初步工作：网络度分布的理论基础和网络同步能力最优的拓扑结构，说明复杂网络需要运筹学的方法和运筹学也需要复杂网络思想。 |
| |
|
| 报告题目： |
Uncover disease genes by maximizing
information flow in the phenome-interactome network |
| 报
告 人： |
江瑞(Jiang Rui) 副教授 清华大学自动化系 |
| 时间地点： |
5月10日（星期二）下午4:00 思源楼1013室 |
| 摘 要： |
Pinpointing genes that underlie human
inherited diseases among candidate genes in susceptibility genetic
regions is the primary step towards the understanding of pathogenesis
of diseases. Although several probabilistic models have been
proposed to prioritize candidate genes using phenotype similarities
and protein-protein interactions, no combinatorial approaches
have been proposed in the literature. We propose the first combinatorial
approach for prioritizing candidate genes. We first construct
a phenome-interactome network by integrating the given phenotype
similarity profile, protein-protein interaction network and
associations between diseases and genes. Then, we introduce
a computational method called MAXIF to maximize the information
flow in this network for uncovering genes that underlie diseases.
We demonstrate the effectiveness of this method in prioritizing
candidate genes through a series of crossvalidation experiments,
and we show the possibility of using this method to identify
diseases with which a query gene may be associated. We demonstrate
the competitive performance of our method through a comparison
with two existing state-of-the-art methods, and we analyze the
robustness of our method with respect to the parameters involved.
As an example application, we apply our method to predict driver
genes in 50 copy number aberration regions of melanoma. Our
method is not only able to identify several driver genes that
have been reported in the literature, it also shed some new
biological insights on the understanding of the modular property
and transcriptional regulation scheme of these driver genes. |
| |
|
| 报告题目： |
Template-free detection of macromolecular
complexes in cryo electron tomograms |
| 报
告 人： |
徐旻(Xu Min) 博士,美国南加州大学分子计算生物学中心 |
| 时间地点： |
5月10日（星期二）下午3:00 思源楼1013室 |
| 摘 要： |
Cryo electron tomography (CryoET)
produces 3D density maps of biological specimen in its near
native states. Applied to small cells cryoET produces 3D snapshots
of the cellular distributions of large complexes. However, retrieving
this information is non-trivial due to the low resolution and
low signal-to-noise ratio in tomograms. Current pattern recognition
methods identify complexes by matching known structures to the
cryo electron tomogram. However, so far only a small fraction
of all protein complexes have been structurally resolved. It
is therefore of great importance to develop template-free methods
for the discovery of previously unknown protein complexes in
cryo electron tomograms.
Here, we have developed an inference method for the template-free
discovery of frequently occurring protein complexes in cryo
electron tomograms. We provide a first proof-of-principle of
the approach and assess its applicability using realistically
simulated tomograms, allowing for the inclusion of noise and
distortions due to missing wedge and electron optical factors.
Our method is a step towards the template-free discovery of
the shapes, abundance and spatial distributions of previously
unknown macromolecular complexes in whole cell tomograms. |
| |
|
| 报告题目： |
High-accuracy network analysis
in systems biology |
| 报
告 人： |
Prof. Katsuhisa Horimoto,Computational
Biology Research Center (CBRC), National Institute of Advanced
Industrial Science and Technology (AIST), Japan |
| 时间地点： |
2011年4月22日（星期五）下午4:00 思源楼1013室 |
| 摘 要： |
The recent development of epoch-making
experimental techniques has enabled measurement of almost all
characteristics of cellular molecules. In general, biological
studies went through a process from the formulation of a hypothesis
to its testing. In systems biology, where the cell is treated
as a system built up of molecules, the progress of experimental
techniques has made it possible to conduct research using actual
measured data. Moreover, the emphasis of research objectives
has moved from exploring the characteristics of molecules to
exploring the associations (networks) among molecules making
up a system. However, this trend toward measuring the characteristics
of huge numbers of molecules constituting cells requires tremendous
expenditures of time and money. It is therefore necessary to
seriously consider for what purpose the measurements are being
made before starting a study, and to ensure high computational
accuracy in analyzing the measurement data to obtain robust
results. Here, we introduce two methods that we have developed
to realize the latter requirement; namely, high computational
accuracy.
The first method is a technique for estimating control networks
that are activated under specific conditions [1-3]. First, for
networks having a particular structure, the statistical quantity
(log-likelihood) is calculated using the values of measured
data. Next, by preparing numerous graphs artificially and calculating
the log-likelihoods of these graphs, the distribution of log-likelihoods
is obtained. Finally, how rarely the log-likelihood of a given
network appears in the distribution, i.e., the graph consistency
probability, is calculated. Using this technique, the functions
possessed by cells in a specific condition can be shown not
merely in a list of the names of genes, but in the form of the
networks consisting of the genes. For this purpose, first the
known networks and the TF (transcriptional factor)-gene binding
data obtained from experiments or databases are prepared. Next,
using the data measured in specific conditions, calculations
are performed to determine which of the prepared networks have
graph consistency probability at a significance level; i.e.,
which networks' forms rarely fit the data under specific conditions.
We have named this procedure "network screening,"
because it selects the networks that appear only in specific
conditions from among a huge number of networks.
The second method is a technique for enhancing the accuracy
of parameter estimation in network dynamics [4,5]. The essence
of this technique is to obtain, from a system of differential
equations presenting network dynamics, another but equivalent
system of differential equations, using mathematics referred
to as differential elimination. The resulting system of differential
equations is adopted as new constraints, together with the error
function typically used in parameter estimation. For the error
function, the difference between the time-course values and
estimated values is considered. On the other hand, since the
new constraints include differentiated values, the form of the
curve provided by the time-course values such as the intercept,
inflection point can be further considered. In fact, this is
an overwhelming improvement compared with the approach using
the conventional error function method. This is a general-purpose
technique in various respects; we aim to apply it not only to
the dynamics of biological phenomena but also to engineering
issues in which parameter estimation is important. |
| |
|
| 报告题目： |
Understanding the Utilization,
Function and Evolution of Trace Elements by Computational and
Comparative Genomics Approaches |
| 报
告 人： |
张焱研究员,中科院上海生命科学研究院 |
| 时间地点： |
2011年4月1日（星期五）下午15:00 思源楼712 |
| 摘 要： |
Biological trace elements are needed
in minute quantities for proper growth, development, and physiology
of all organisms. These micronutrients provide proteins with
unique coordination, catalytic, structural, electron transfer
and other properties in a variety of pathways. Utilization of
trace elements is generally rather complex and a growing number
of trace element-dependent proteins and trace element utilization
pathways highlights importance of these elements for life. In
recent years, dramatic advances in genomics and related studies
provided an opportunity to investigate the occurrence and evolution
of numerous biochemical pathways that an organism utilizes,
including trace element utilization. Our studies focus on several
important trace elements, such as selenium, zinc, iron, copper,
nickel, cobalt and molybdenum. A variety of systematic, genome-wide
computational and comparative approaches have been used for
the analysis of these elements, which provide important information
with regard to fundamental issues of their function and evolutionary
dynamics of trace element utilization in biology. |
| |
|
| 报告题目： |
Numerical approach to structure
and folding of protein and microRNA |
| 报
告 人： |
胡进锟(Chin-Kun Hu)教授,台湾“中央研究院”物理研究所 |
| 时间地点： |
2011年4月1日（星期五）下午14:00 思源楼712 |
| 摘 要： |
In this talk, I briefly review some
recent developments in numerical approach to structure and folding
of proteins and microRNA. The topics under discussion include:
(1) developments of algorithms and computer packages for all-atom
simulations of proteins [1], (2) development of algorithm to
compute volume V, surface area A, and cavity of proteins by
analytic equations [2], (3) unfolding and refolding of immunoglobulin
domain I27 and ubiquitin [3], and (4) TAROKO: a webserver for
microRNA 3D structures and folding thermodynamics [4].
- (1) F. Eisenmenger, U. H.E. Hansmann, S. Hayryan, and
C.-K. Hu. Computer Phys. Commu. 138, 192-212 (2001) and
174, 422 (2006); C.-Y. Lin, C.-K. Hu, and U.H.E. Hansmann,
Proteins 52, 436-445 (2003); S. Hayrian, C.-K. Hu, S.-Y.
Hu and R.-J. Shang. J. Comp. Chem. 22, 1287-1296 (2001);
R. G. Ghulghazaryan, S. Hayryan and C.-K. Hu. J. Comp. Chem.,
28, 715 (2007).
- (2) S. Hayryan, C.-K. Hu, J. Skvrivanek, E. Hayrjan, I.
Pokorny. J. Comp. Chem. 26, 334 (2005); J. Busa, J. Dzurina,
E. Hayryan, S. Hayryan, C.-K. Hu, J. Plavka, I. Pokorny,
J. Skrivanek, and M-C. Wu. Comp. Phys. Commun. 165, 59 (2005);
J. Busa,, S. Hayryan, C.-K. Hu, J. Skrivanek, and M.-C.
Wu, J. Comp. Chem. 30, 346-357 (2009) and Comp. Phys. Commun.
181, 2116 (2010).
- (3) M.-S. Li, C.-K. Hu, D. K. Klimov, and D. Thirumalai,
Proc. Natl. Acad. Sci. USA 103, 93 (2006); M.-S. Li, M.
Kouza and C.-K. Hu. Biophysical J. 91, 547(2007). M. Kouza,
C.-K. Hu and M. S. Li, J. Chem. Phys 128, 045103 (2008).
- (4) S. Harryan, M.-C. Wu, F. Ding, D. Tsao, N. V. Dokholyan
and C.-K. Hu, submitted for publication.
|
| |
|
| 报告题目： |
Simple
models to uncover key factors for protein aggregation |
| 报
告 人： |
胡进锟(Chin-Kun Hu)教授,台湾“中央研究院”物理研究所 |
| 时间地点： |
2011年3月24日（星期四）上午10:00 思源楼1013 |
| 摘 要： |
Neurodegenerative diseases include
Alzheimer's disease (AD), Huntington's disease (HD)， etc. Such
diseases are due to progressive loss of structure or function
of neurons caused by protein aggregation. For example, AD is
considered to be related to aggregation of Aβ40 and Aβ42 (protein
with 42 amino acids). In this talk, I briefly review our recent
discovery on key factors for protein aggregation. We have used
a lattice model to study the aggregation rates of proteins and
found that the probability for a protein sequence to appear
in the conformation of the aggregated state can be used to determine
the temperature at which proteins can aggregate most easily
[1].
We have used molecular dynamics and simple models of polymer
chains to study relaxation and aggregation of proteins under
various conditions and found that when the bending-angle dependent
and torsion-angle dependent interactions are zero or very small,
then protein chains tend to aggregate at lower temperatures
[2]. Such result is useful for understanding aggregation of
Aβ40 and Aβ42. Our results [1,2] form good basis for further
studies on protein aggregation.
[1] M. S. Li, N. T. Co, G. Reddy, C. -K. Hu, J. E. Straub,
and D. Thirumalai, Phys. Rev. Lett. 105, 218101(2010).
[2] W.-J. Ma and C.-K. Hu, J. Phys. Soc. Japan 79, 024005,
024006, 054001, and 104002 (2010).
|
| |
|
| 报告题目： |
计算生物学中的学习方法 |
| 报
告 人： |
郭茂祖 教授,哈尔滨工业大学计算机学院 |
| 时间地点： |
10月30日上午（星期六）10：00 思源楼1013室 |
| 摘 要： |
计算生物学中的算法主要涉及串、树、图等组合算法，以及机器学习等人工智能方法。简要介绍RNA结构预测与挖掘、基因组序列多态性（SNP）分析、蛋白质相互作用（PPI）预测中与机器学习相关的正反训练集划分、特征选择、学习算法等。 |
| |
|
| 报
告 人： |
Prof.
Kwang-Hyun Cho,Department of Bio and Brain Engineering, Korea
Advanced Institute of Science and Technology (KAIST) |
| 时间地点： |
7月27日（星期二）下午16:00
思源楼1013室 |
| 摘 要： |
Most biological
networks have huge complex structures which daunt us to make
any sense of them. A question then arises as to whether there
exists an essential core subnetwork that actually realizes
most of the key regulatory functions and forms a backbone
structure, within such a large complex network. We have developed
an algorithm by which we can identify such a core structure
in consideration of the relationship between network topology
and dynamics. Intriguingly, we found that such core structures
preserve all the fundamental network dynamics and include
most of the biologically important nodes. The proposed concept
of a core network can provide us with new insights into the
evolutionary design principle of complex biological networks.
|
| |
|
| 报告题目： |
Maximum
Entropy Principle for Composition Vector Method in Phylogenetics |
| 报
告 人： |
Prof.
Raymond H. Chan，Department of Mathematics, The Chinese University
of Hong Kong |
| 时间地点： |
4月29日（星期四）上午10:30
思源楼712室 |
| 摘 要： |
Molecular
Phylogenetics is the study of evolutionary relatedness among
species through molecular sequencing data. The composition vector
(CV) method is an alignment-free method for phylogenetics. Since
biological sequences are often obscured by noise and bias, denoising
is necessary when using the CV method. By using the maximum
entropy principle for denoising and utilizing the special structure
of the constraint matrix to simplify the optimization, we derive
several new denoising formulas. By comparing with existing formulas
on ten different data sets, we found that one of our formulas
gives more accurate phylogenetic trees. An example is the tree
for the tetrapod data set where we can correctly group birds
and reptiles together, a result that cannot be obtained previously
by either alignment method or other denoising formulas |
| |
|
| 报告题目： |
Improving
protein binding sites prediction with consensus approaches |
| 报
告 人： |
Dr.
Bingding Huang,Senior Researcher, Bioinformatics group, Biotec,
TU Dresden, Dresden. Systems Biolgy Division, Zhejiang-California
International Nanosystems Institute (ZCNI), Zhejiang University |
| 时间地点： |
4月15日（星期四）下午3:00
思源楼712室 |
| 摘 要： |
In
the last decades, many computational efforts have been done
to predict protein binding sites based on protein structure
and resulted in a lot of algorithms, software and web-servers.
In this talk, I will present two meta-approaches to predict
protein-ligand binding sites and protein-protein interaction
sites: metaPocket and metaPPI. MetaPocket uses the predicted
pocket sites from four methods: LIGSITEcs, PASS, Q-SiteFinder,
and SURFNET to improve the prediction success rate from 70%
to 75% at the top 1 prediction. For protein-protein binding
site prediction, metaPPI includes PPI-Pred, PPISP, PINUP, Promate
and SPPIDER, which predict enzyme-inhibitor interfaces with
success rates of 23% to 55% and other interfaces with 10% to
28% on a benchmark dataset of 62 complexes. MetaPPI significantly
improves prediction success rates to 70% for enzyme-inhibitor
and 44% for other interfaces. |
| |
|
| 报告题目： |
Dynamical
Systems Analysis of Prostate Cancer |
| 报
告 人： |
Prof.
Kazuyuki Aihara，Institute of Industrial Science, The University
of Tokyo |
| 时间地点： |
3月29日（星期一）上午10:00
思源楼712室 |
| 摘 要： |
Prostate cancer
is recently becoming a serious social problem. It is the secondly
most common cancer in men. Although the incident rate of prostate
cancer is not so high in Asian countries like China and Japan
fortunately, its increasing rate is highest among cancers
of the Japanese men. In this talk, I review our dynamical
systems approach to prostate cancer and its therapy based
on mathematical modeling.
References
(1) A.M. Ideta, G. Tanaka, T. Takeuchi, and K. Aihara: J.
Nonlinear Science, Vol.18, No.6, pp.593-614 (2008).
(2) G. Tanaka, K. Tsumoto, S. Tsuji, and K. Aihara: Physica
D, Vol.237, No.20, pp.2616-2627 (2008).
(3) T. Shimada and K. Aihara: Mathematical Biosciences, Vol.214,
No.1/2, pp.134-139 (2008).
(4) Y. Tao, Q. Guo, and K. Aihara, J. Nonlinear Science (in
press)
Kazuyuki Aihara
received the B.E. degree in electrical engineering in 1977
and the Ph.D. degree in electronic engineering 1982 from the
University of Tokyo, Tokyo, Japan. Currently, he is Professor
in Institute of Industrial Science, Graduate School of Information
Science and Technology, and Graduate School of Engineering,
the University of Tokyo. His research interests include mathematical
modeling of complex systems, parallel distributed processing
with chaotic neural networks, and nonlinear time series analysis.
|
| |
|
| 报告题目： |
Mathematical
modelling and computational analysis of protein folding |
| 报
告 人： |
Prof.
Christof Schuette,Freie Universitaet Berlin德国柏林自由大学 |
| 时间地点： |
3月19日（星期五）下午2:00,思源楼1013室 |
| 摘 要： |
Characterizing
the equilibrium ensemble of folding pathways, including their
relative probability, is one of the major challenges in protein
folding theory today. Although this information is in principle
accessible via all-atom molecular dynamics simulations, it is
difficult to compute in practice because protein folding is
a rare event and the affordable simulation length is typically
not sufficient to observe an appreciable number of folding events,
unless very simplified protein models are used. Here we present
an approach that allows for the reconstruction of the full ensemble
of folding pathways from simulations that are much shorter than
the folding time. This approach is based on partitioning the
state space into small conformational states and constructing
a Markov model between them. The talk will presented the mathematical
theory that allows for the extraction of the full ensemble of
transition pathways from the unfolded to the folded configurations,
and can be likewise applied to many other complex systems exhibiting
metastable effective dynamics. The approach will then be applied
to the folding of a small protein, the PinWW domain in explicit
solvent, where the folding time is two orders of magnitude larger
than the length of individual simulations. The results are in
good agreement with kinetic experimental data and give detailed
insights about the nature of the folding process which is shown
to be surprisingly complex and parallel. The analysis reveals
the existence of misfolded trap states outside the network of
efficient folding intermediates that significantly reduce the
folding speed.
Prof. Christof
Schuette is a full professor in mathematics at Freie Universitaet
Berlin. His speciality is biocomputing. He is one of the Directors
of the Berlin Mathematical School - a joint top graduate school
in mathematics of the research universities in Berlin - as
well as the Vice Director of the Research Center MATHEON -
Mathematics for Key Technologies - funded by the German Science
Foundation (DFG) as a center for excellence.
|
2009年
|
| 报告题目： |
Quantitative
Simulation for Biomolecular Networks |
| 报
告 人： |
Prof.
Luonan Chen，Osaka Sangyo University |
| 时间地点： |
7月22日（星期三）下午2:00
思源楼1013室 |
| 摘 要： |
Explicitly
considering all variables and chemical reactions in a cell is
unrealistic for a biomolecular network from modeling, analyzing
and computing viewpoint. However, in a cell, many different
time scales characterize the gene regulatory processes, which
can be exploited to reduce the complexity of the mathematical
models. For instance, the transcription and translation processes
generally evolve on a time scale that is much slower than that
of phosphorylation, dimerization or binding reactions of transcription
factors. Moreover, in biological systems, a large class of biological
models can be approximately by stochastic hybrid systems in
which some state components are discrete and other are continuous.
Continuous state components are usually involved in fast reactions
with high copy numbers of molecules, whereas discrete state
components are in slow processes and have low copy numbers of
molecules. In this work, based on the partial Kramers-Moyal
expansion with the central limit theorem, we exploit such properties
to simplify a complicated molecular network to a hybrid system
by giving several models, which can be applied to the quantitative
simulation of a large cellular system. we developed a novel
stochastic hybrid model for representing chemical master equation,
and provided several computational algorithms to efficiently
simulate the stochastically cellular dynamics. |
| |
|
| 报告题目： |
Emerging
of Stochastic Dynamical Equalities and Steady State Thermodynamics
from Darwinian Dynamics |
| 报
告 人： |
敖平
教授 (上海交通大学系统生物医学院) |
| 时间地点： |
2009.6.23(星期二)，10：00，思源楼712室 |
| 摘 要： |
The evolutionary
dynamics first conceived by Darwin and Wallace, referring
to as Darwinian dynamics in the present paper, has been found
to be universally valid in biology. The statistical mechanics
and thermodynamics, while enormous successful in physics,
have been in an awkward situation of wanting a consistent
dynamical understanding. Here we present from a formal point
of view an exploration of the connection between thermodynamics
and Darwinian dynamics and a few related topics. We first
show that the stochasticity in Darwinian dynamics implies
the existence temperature, hence the canonical distribution
of Boltzmann-Gibbs type. In term of relative entropy the Second
Law of thermodynamics is dynamically demonstrated without
detailed balance condition, and is valid regardless of size
of the system. In particular, the dynamical component responsible
for breaking detailed balance condition does not contribute
to the change of the relative entropy. Two types of stochastic
dynamical equalities of current interest are explicitly discussed
in the present approach: One is based on Feynman-Kac formula
and another is a generalization of Einstein relation. Both
are directly accessible to experimental tests. Our demonstration
indicates that Darwinian dynamics represents logically a simple
and straightforward starting point for statistical mechanics
and thermodynamics and is complementary to and consistent
with conservative dynamics that dominates the physical sciences.
Present exploration suggests the existence of a unified stochastic
dynamical framework both near and far from equilibrium.
敖平，1983年获北京大学物理学学士。1985年获美国伊利诺大学香槟分校(University of Illinois
at Urbana-Champaign, UIUC)物理学硕士。1990年获UIUC物理学博士学位，导师为诺贝尔奖获得者Prof.
A. J. Leggett。1990-1994年在美国华盛顿大学(University of Washington)物理系从事博士后研究，合作导师为美国科学院院士Prof.
D. J. Thouless。1994-2000年任瑞典Umea大学物理系副教授。2000-2003年任西雅图的美国系统生物学研究所(United
States Institute for Systems Biology)高级研究科学家及访问教授，与研究所创始人之一美国科学院院士Leory
Hood进行合作研究。2003-2008年任华盛顿大学机械工程系副教授。2008年回国任上海交通大学系统生物医学院特聘教授,
973肥胖症项目首席科学家.
|
| |
|
| 报告题目： |
Integrative
disease classification and phenotype prediction based on cross-platform
microarray data |
| 报
告 人： |
Dr.
Chun-Chi Jim Liu (Molecular and Computational Biology, University
of Southern California) |
| 时间地点： |
2009.1.12
(星期一), 15:00 思源楼712教室 |
| 摘 要： |
.
|
|
|
| 报告题目： |
Boolean
Models and Algorithms for Analyzing Genetic Networks and Metabolic
Networks |
| 报
告 人： |
Prof.
Tatsuya Akutsu (Bioinformatics Center, Institute for Chemical
Research, Kyoto University) |
| 时间地点： |
2009.1.12(星期一),
10:00 思源楼712教室 |
| 摘 要： |
.
|
|
2008年
|
| 报告题目： |
Knowledge-based
Approaches for Reconstruction of Biological Networks |
| 报
告 人： |
Prof.
Yang Dai (Department of Bioengineering University of Illinois
at Chicago) |
| 时间地点： |
2008.7.14
(星期一), 15:00 思源楼1013教室 |
| 摘 要： |
.
|
|
2007年
|
| 报告题目： |
Mathematical
modeling of circadian rhythms |
| 报
告 人： |
Prof.
Albert Goldbeter (Université Libre de Bruxelles, Belgium) |
| 时间地点： |
2007.5.30
(星期三), 15:30 思源楼1013教室 |
| 摘 要： |
Circadian oscillations
occur spontaneously with a period of about 24 h in nearly
all living organisms. These oscillations originate from intertwined
feedback processes in genetic regulatory networks. Based on
experimental observations, mathematical models of increasing
complexity have been proposed for the molecular mechanism
of circadian rhythms. Deterministic models were first proposed
for circadian rhythms in Drosophila. These models account
for the occurrence of sustained oscillations of the limit
cycle type and for a variety of dynamical properties such
as phase shifting or long-term suppression by light pulses
and entrainment by light-dark cycles. Stochastic versions
of the models are needed to examine how molecular noise affects
the emergence and robustness of circadian oscillations. Extending
the model to the case of the mammalian circadian clock allows
us to address the dynamical bases of physiological disorders
of the sleep-wake cycle in humans.
References :
Leloup, J.C. and
Goldbeter, A. 2003. Toward a detailed computational model
for the mammalian circadian clock. Proc. Natl. Acad. Sci.
USA 100, 7051-7056.
Leloup, J.C. and
Goldbeter, A. 2004. Modeling the mammalian circadian clock
: Sensitivity analysis and multiplicity of oscillatory mechanisms.
J. Theor. Biol. 230, 541-562.
|
|
2006年
|
| 报告题目： |
A
Knowledge-Based, Statistical Informatics Approach for Protein
Structure Refinement |
| 报
告 人： |
Prof.
Zhijun Wu (Department of Mathematics, Program on Bioinformatics
and Computational Biology Iowa State University, USA ) |
| 时间地点： |
2006.12.21
(星期四), 15:00 思源楼712教室 |
| 摘 要： |
The
protein structures determined by conventional techniques usually
are not as accurate as desired. Further refinement including
human intervention is always required and sometimes critical.
Therefore, the development of an efficient refinement technique
is important, and as more and more structures are determined,
the need is even more urgent, as the CASP prediction center
explained for the call for a structure refinement competition
in spring 2006. Here, we describe a computational approach of
deriving distance constraints from databases of known protein
structures for structure refinement. We calculate the distributions
of the distances of various types in known protein structures,
and use them to obtain the most probable ranges or the mean-force
potentials for the distances. We then impose the constraints
on the structures to be refined or include the mean-force potentials
in energy minimization so that more plausible structural models
may be built. We show that many inter-atomic distances in low-resolution
structures deviate significantly from their average distributions
in known protein structures, and the structures can be refined
when a selected set of distances are constrained to their most
probable ranges or optimized with corresponding mean-force potentials.
We present the results from refining a set of NMR-determined
protein structures by using database derived distance constraints
and mean-force potentials, and show the improvements on the
structures in terms of several standard measures. We also discuss
our results from participating in the CASPR 2006 structural
refinement experiments for comparative model refinement, using
energy minimization, database derived distance constraints,
and massively parallel computing. We describe the development
of a database of protein inter-atomic distances that supports
computing the distributions of the distances of various types
in known protein structures and generating the constraints or
potentials for the distances automatically. We discuss the possibilities
of extending the system to a broader sense of protein geometry
database and using it for structure analysis, classification,
as well as refinement. |
|
|
|
| 报告题目： |
Evolutionary
matching of surface patterns for predicting protein functions
and binding specificities |
| 报
告 人： |
Prof.
Jie Liang （Department of Bioengineering University of Illinois
at Chicago, USA Institute of Systems Biomedicine Shanghai Jiaotong
University, CHINA ) |
| 时间地点： |
2006.10.27
(星期五), 15:00 思源楼712教室 |
| 摘 要： |
Predicting
protein functions is a challenging task, as evolutionary relationship
reflected by global
sequence and structure similarities are often unreliable for
function prediction. For proteins binding to similar substrates
or ligands and carrying out similar functions, their binding
surfaces experience similar physicochemical constraints, and
hence the sets of allowed and forbidden residue substitutions
are similar. We develop a method for predicting protein functions
by incorporating evolutionary information specific to an individual
binding region and by rapidly matching local surfaces. Our method
is based on the estimation of substitution rates of amino acids.
It computes a profile which characterizes protein binding activities
that may involve multiple substrates or ligands. We show that
our method can be used to predict enzyme functions, to identify
potential substrates, and to assess binding specificity. In
an objective large
scale test of 100 enzyme families with 2,196 structures, our
predictions are sensitive and specific: At the stringent specificity
level of 99.98%, we can correctly predict enzyme functions for
80.55% of the proteins. The overall area under the Receiver
Operating Characteristic curve measuring the performance of
our prediction is 0.955. Our method also works well in predicting
the biochemical functions of orphan proteins from structural
genomics project. |
|
|
| 报告题目： |
Multiple
Sequence Alignment Using Partial Order Graphs |
| 报
告 人： |
Dr.
Christopher Lee（Chemistry & Biochemistry Department University
of California at Los Angeles, USA ) |
| 时间地点： |
2006.8.30
(星期三), 15:00 思源楼712教室 |
| 摘 要： |
|
|
|
| 报告题目： |
Inferring
Protein Interactions with Correlated Domains by Integrative
Databases |
| 报
告 人： |
Prof.
Luonan Chen（Osaka Sangyo University, Japan ) |
| 时间地点： |
2006.8.23
(星期三), 15:00 思源楼712教室 |
| 摘 要： |
|
|
|
| 报告题目： |
A
Systems Biology Approach for Studying Gene Function and Pathway
through Mining Functional Genomic Data |
| 报
告 人： |
Prof.
Dong Xu（Digital Biology Laboratory, Computer Science Department
and Life Sciences Center, University of Missouri-Columbia, Columbia,
MO, USA ) |
| 时间地点： |
2006.5.31
(星期三), 15:00 思源楼712教室 |
| 摘 要： |
We
have developed a number of computational approaches to infer
gene function and pathway through utilizing various functional
genomic data, including protein-protein interactions, protein
complexes, microarray data, and genomic sequences. We quantify
the relationship between functional similarity in the Gene Ontology
biological process and functional data, and coded the relationship
into a "functional linkage graph", where each node
represents one gene and the weight of each edge is characterized
by the Bayesian probability of function similarity between the
two connected genes. We utilized the graph to predict gene function
and signaling pathways in yeast and Arabidopsis. We also analyzed
Arabidopsis tiling array data to predict anti-sense gene silencing
and validated the prediction using EST data. Some anti-sense
predictions were confirmed through RT-PCR. |
|
|
| 报告题目： |
Mathematical
analysis of genetic network: Function, Dynamics and Noise |
| 报
告 人： |
Dr.
Sanyi Tang(Warwick University, UK ) |
| 时间地点： |
2005.12.01 (星期四), 15:00 晨兴510室 |
| 摘 要： |
|
|
2005年
|
| 报告题目： |
计算模型与复杂适应系统 |
| 报
告 人： |
张江 博士(北京交通大学经济管理学院 ) |
| 时间地点： |
2005.11.01 (星期二), 15:30 思源楼712室 |
| 摘 要： |
计算模型是研究复杂适应系统的主要手段之一，它不仅可以对复杂系统进行模拟和仿真，提供一种可操作的试验平台，而且可以用隐喻的方法为人们提供对复杂适应系统的深刻洞察。本报告主要介绍width我开发的两个计算模型：Autolife和AEM。Autolife是一个数字人工生命系统，运用该模型我们可以研究Agent个体的进化行为、群体的适应性行为、生命和环境的关系，以及组织的涌现、演化、社会性寄生和自修复等现象。AEM是一个模拟的经济系统，从著名的人工社会模型Sugarscape扩展得来。Agent的层级适应性决策建模技术使得我们可以探讨虚拟经济系统的价格波动、社会分工、市场组织的形成与演化、交易网络、Agent流和商品流的形成与演化等规律。 |
|
|
| 报告题目： |
DNA
Screening and Pooling Designs |
| 报
告 人： |
Prof. Ding-Zhu
Du (University of Texas at Dallas )
|
| 时间地点： |
2005.11.01
(星期二), 14:30 思源楼712室 |
| 摘 要： |
A
recent important development in biology is the success of Human
Genome Project. As the technology for obtaining sequenced genome
data is getting mature, more and more sequenced genome data
are available to scientific research community, so that the
study of gene functions has become a popular research direction.
The study of gene functions requires to obtain DNA library of
high quality through a large amount of testing and screening.
Pooling design is a mathematical tool to reduce the number of
tests for DNA library screening. In this talk, we introduce
a new method to construct pooling designs. |
|