SMIDTAS Serge
my biological findings & discoveries homepage
Biology - Physics - Informatic & Modelisation -
2002-2008
Intro
Modelisation and Alalysis of Local and Global Networks of Biological Heterogeneous Interactions, Applied to Yeast.
2003 Hybrigenics FR
2007 CEA FR
Evry University
Serge Smidtas
Ecole doctorale: Des Genomes aux organismes
Thesis director:Francois Kepes , Vincent Schachter
.
Le jury a apprécié l'exposé oral structuré, clair, et pédagogique qyu éclairait la cohérence de l'ensemble des travaux du candidat. Il a montré sa maitrise à la foi des questions biologiques, de modélisation et d'outils informatiques, pendant l'oral ainsi que pendant la réponse au jury. Son exposé a ainsi révélé la créativité que l'on trouvait dans son travail. Mention Très honorable.
J.P. Mazat Pr Bordeaux 2, O. Martin Pr. Paris 11, O. Poch Dir. Rech. Strasbourg 1, P. Bourgine Ing X, F. Kepes Dir. Rech. Genopole, H. Klaudel Pr Evry, J.P.
pdf -
pdf -
Hal -
SciVerse
Modeling of the Lambda Phage Genetic Switch
Yartseva Anastasia et collaborateurs dont Serge Smidtas.
ISBN-13: 978-1411695450
url
A 20cm Escherichia coli model
How would Escherichia coli look like standing on your desk?
Escherichia coli (E. coli), is one of the main species of bacteria that live in the lower intestines of mammals
including us. T$necessary for the proper digestion of food and are part of the intestinal flora. The bacteria ferments
lactose with the product$is released as flatulence.
The human body has the same number of human cell and e.coli cells: 10 000 000 000 000. Buy one of 20cm long, magnified
one mill$protein can be seen. Each molecular component is reproduced (see table bellow) with the same characteristics.
You will be aston$much DNA, proteins, and others parts are big. Astonish your visitors, friends and students.
url
Prizes & Grants
European Grant, GIACS
2005-11, ISI Torino, Italy
NEST - GIACS. General Integration of the Applications of Complexity in Science.
GIACS - ISI -
Complexity research
Synthetic Biology
2007-11, 1st place for Foundational Researg, iGEM, MIT, USA
iGEM
Diplom1, Diplom2, Gold
ECCS 2005 Best poster award
2005, Paris, France
Incremental and unifying modeling formalism for biological interaction networks
Anastasia Yartseva, Smidtas Serge, Hanna Klaudel, Francois Kepes
ECCS05 Prize -
Papers
CycSim - an online tool for exploring and experimenting with genome-scale metabolic models.
Le Fèvre F, Smidtas S, Combe C, Durot M, d'Alché-Buc F, Schachter V.
CEA, DSV, IG, Genoscope, UMR 8030, Evry, F-91057, France
Bioinformatics. 2009 May 6
CycSim is a web application dedicated to in silico experiments with genome-scale metabolic models coupled to the exploration of knowledge from BioCyc and KEGG. Specifically, CycSim supports the design of knockout experiments: simulation of growth phenotypes of single or multiple gene deletions mutants on specified media, comparison of these predictions with experimental phenotypes, and direct visualization of both on metabolic maps. The web interface is designed for simplicity, putting constraint-based modelling techniques within easier reach of biologists. CycSim also functions as an online repository of genome-scale metabolic models.
doi:10.1093/bioinformatics/btp268
- online tool
The adaptative filter of the yeast galactose pathway
S. Smidtas, V. Schachter, F. Kepes
Journal of Theoretical Biology 2005
Received 12 September 2005; received in revised form 20 February 2006; accepted 10 March 2006
In the yeast Saccharomyces cerevisiae, the interplay between galactose, Gal3p, Gal80p and Gal4p determines the transcriptional status of the genes required for galactose utilization. After an increase in galactose concentration, galactose molecules bind onto Gal3p. This event leads via Gal80p to the activation of Gal4p, which then induces GAL3 and GAL80 gene transcription. Here we propose a qualitative dynamic model, whereby these molecular interaction events represent the first two stages of a functional feedback loop that closes with the capture of activated Gal4p by newly synthesized Gal3p and Gal80p, decreasing transcriptional activation and creating again the protein complex that can bind incoming galactose molecules. Based on the differential time scales of faster protein interactions versus slower biosynthetic steps, this feedback loop functions as a derivative filter where galactose is the input step signal, and released Gal4p is the output derivative signal. One advantage of such a derivative filter is that GAL genes are expressed in proportion to the cellular requirement. Furthermore, this filter adaptively protects the cellular receptors from saturation by galactose, allowing cells to remain sensitive to variations in galactose concentrations rather than to absolute concentrations. Finally, this feedback loop, by allowing phosphorylation of some active Gal4p, may be essential to initiate the subsequent long-term response.
PDF -
JTB -
doi:10.1016/j.jtbi.2006.03.005 -
PMID-16643954
q-bio.MN/0604012
Cyclone : Java-based querying and computing with Pathway/Genome Databases
François Le Fèvre, Serge Smidtas, Vincent Schächter
Transactions on
Bioinformatics 2007 doi: 10.1093/bioinformatics/btm107
Cyclone aims at facilitating the use of BioCyc, a collection of Pathway/Genome Databases (PGDBs). Cyclone provides a fully extensible Java Object API to analyze and visualize these data. Cyclone can read and write PGDBs. It , and can write its own data in the CycloneML format. This format. The latter is automatically generated from the BioCyc ontology by Cyclone itself, ensuring continued compatibility. Since Cyclone objects can also be stored in a relational database, CycloneDB., Qqueries can be written in SQL, and in an oObject-oriented qQuery lLanguage, (HOQL), an intuitive and concise query language. In addition, Cyclone interfaces easily with Java software including the Eclipse IDE for HOQL edition, Jung API for graph algorithms or Cytoscape for graph visualization.
Bioinformatics
- DOI: 10.1093/bioinformatics/btm107 -
Property-driven statistics of biological networks
P.Y. Bourguignon, V. Danos, F. Kepes, V. Schachter, S. Smidtas
Transactions on
Computational Systems Biology VI. Lecture Notes in Computer Science 4220 Springer 2006, ISBN 3-540-45779-8
An analysis of heterogeneous biological networks based on randomizations
that preserve the structure of component subgraphs is introduced and applied to the yeast
protein-protein interaction and transcriptional regulation interaction network. Shuffling
this network, under the constraint that the transcriptional and protein-protein interaction
subgraphs are preserved reveals statistically significant properties with potential biological
relevance. Within the population of networks which embed the same two original compo-
nent networks, the real one exhibits simultaneously higher bi-connectivity (the amount of
pairs of nodes which are connected using both subgraphs), and higher distances. More-
over, using restricted forms of shuffling that preserve the interface between component
networks, we show that these two properties are independent: restricted shuffles tend to
be more compact, yet do not lose any bi-connectivity.
Finally, we propose an interpretation of the above properties in terms of the signalling
capabilities of the underlying network.
Paper v1,v2 - LNCS
- DOI: 10.1007/11880646_1 - Book chapter PDF
Model of Interactions in Biology and Application to Heterogeneous Network in Yeast.
Smidtas S., Yartseva A., Scachter V., Kepes F.
Compte Rendus de l'Accadémie des Sciences - Biologies, 2006
A major challenge for bioinformatics and theoretical biology is to build and analyse a unified model
of biological knowledge resulting from high throughput experiment data. Former work analyzed hetero-
geneous data (protein-protein interactions, genetic regulation, metabolism, synexpression) by modelling
them by graphs. These models are unable to represent the qualitative dynamics of the reactions or to
model the n-ary interactions. Here, MIB, a bipartite model of biological networks, is introduced, and its
use for topological analysis of the heterogeneous network is presented. Heterogeneous loops and links
between synexpression pattern and underlying molecular mechanisms are proposed.
doi:10.1016/j.crvi.2006.06.010PDF - CRASS - Supplementary
materials
Learning local gene interaction networks from noisy expression data with
probabilistic graphical models
V. Schachter, V. Danos, S. Smidtas, F. Kepes
Computational Methods in Systems Biology CMSB 2005 Long Paper
3-5 April 2005, Edinburgh, Scotland
An analysis of biological networks based on property-preserving
randomizations is presented. Unlike any other method proposed yet, ours
assumes no preliminary notion of random network and is not limited to the
detection of local properties. The feasibility and relevance of the method
are demonstrated in the yeast protein-protein interaction and
transcriptional regulation interaction network. A measure of modularity is
proposed revealing a significant deviation between the real network and the
randomized versions.
PDF -
Conference
- Archive
First French team success during iGEM Synthetic biology competition
L'équipe iGEM Paris*. (*) including Serge Smidtas
Medecine Science. 2008 May;24(5):541-544.
Cette année, la compétition iGEM a été divisée en 5 parcours à thème :
Médecine et Santé, Environnement, Énergie, Traitement de l'Information et
Recherche Fondamentale. C'est dans cette dernière catégorie que l'équipe
francilienne a concouru avec pour projet de construire une bactérie mul-
ticellulaire synthétique. L'organisme imaginé est multicellulaire en ceci
qu'il est composé de deux types cellulaires interdépendants (Figure 2).
L'un, dédié à la reproduction (nommé lignée germinale), ne peut survivre
qu'en présence du second type (la lignée somatique) qui provient par
différenciation du premier. Cette dépendance vient de ce que les cellules
germinales requièrent du diaminopimélate (DAP) pour la synthèse de leur
paroi. Or le DAP leur est fourni par les cellules somatiques capables, elles,
de le surproduire. Les cellules somatiques sont en revanche incapables de
se diviser. Leur existence dépend donc entièrement de la différenciation
de cellules de la lignée germinale. Ainsi l'interdépendance des deux types
cellulaires est assurée. une place en finale.
PubMed 18466734
- PDF -
Journal
Iterative reconstruction of a global metabolic model of Acinetobacter baylyi ADP1 using high-throughput growth phenotype and gene essentiality data.
Durot M, Le Fèvre F, de Berardinis V, Kreimeyer A, Vallenet D, Combe C, Smidtas S, Salanoubat M, Weissenbach J, Schachter V
BMC Syst Biol. 2008 Oct 7;2:85
BACKGROUND: Genome-scale metabolic models are powerful tools to study global properties of metabolic networks. They provide a way to integrate various types of biological information in a single framework, providing a structured representation of available knowledge on the metabolism of the respective species. RESULTS: We reconstructed a constraint-based metabolic model of Acinetobacter baylyi ADP1, a soil bacterium of interest for environmental and biotechnological applications with large-spectrum biodegradation capabilities. Following initial reconstruction from genome annotation and the literature, we iteratively refined the model by comparing its predictions with the results of large-scale experiments: (1) high-throughput growth phenotypes of the wild-type strain on 190 distinct environments, (2) genome-wide gene essentialities from a knockout mutant library, and (3) large-scale growth phenotypes of all mutant strains on 8 minimal media. Out of 1412 predictions, 1262 were initially consistent with our experimental observations. Inconsistencies were systematically examined, leading in 65 cases to model corrections. The predictions of the final version of the model, which included three rounds of refinements, are consistent with the experimental results for (1) 91% of the wild-type growth phenotypes, (2) 94% of the gene essentiality results, and (3) 94% of the mutant growth phenotypes. To facilitate the exploitation of the metabolic model, we provide a web interface allowing online predictions and visualization of results on metabolic maps. CONCLUSION: The iterative reconstruction procedure led to significant model improvements, showing that genome-wide mutant phenotypes on several media can significantly facilitate the transition from genome annotation to a high-quality model.
PMID: 18840283 -
10.1186/1752-0509-2-85
Rooting a Graph by the Environment Interface Applied to Heterogeneous Interaction Network of the Yeast
Anastasia Yartseva, Serge Smidtas
Journal Acta Biotheoretica (accepted, 2007)
Many natural phenomena in natural and social
sciences, finance and technology are not isolated and should
be studied together with their environment. Thus, they may
be modeled as a pair of interacting graphs. Here, we characterize the interaction between two graphs sharing common
nodes, and for each graph a layered structure respective to
their interface is defined. We apply this analysis method to the
biological interaction network of the yeast.
Results: We demonstrated that the rooting procedure provides an interesting tool to study interacting networks. We
showed that the genetic regulator y network and the proteinprotein interaction network of the yeast had a non-trivial
topology of the interface structure. A node position within
obtained network layers was correlated with the intracellular
PDF
How to study cooperativity, coupling and inter-relations of large networks. (Work in Progress)
Serge SMIDTAS
2005-08
The past few years have witnessed a hectic activity devoted to the characterization and
understanding of networked structures as diverse as ecological and biological systems or the
Internet 1. These networks generally exhibit complex topological properties such as the small-
world phenomenon 2 and scale-free behavior. The need for explaining these complex
topological features has led to a new modeling framework that focuses on the topological
study of networks. In this perspective, a wide array of analysis aimed at capturing various
properties of real networks have been formulated. These models, however, do generally
consider only one network at a time and do not study two (or more) cooperative of such
networks, for example, the diversity of the biological interaction, social networks, or
technological networks. In social systems, the network of scientific papers linked by common
authors and the directed network of papers that cite other papers are two graphs that do not
represent the same information but are obviously not independent. Similarly, the network of
Protein-Protein Interactions (representing physical interactions between proteins), and the
directed Transcriptional Regulation Network (representing proteins (genes) regulating the
expression of other proteins (genes)) work together in biological cells. An other example is
the competitive airline networks of two airlines alliances. Interestingly, studies have tried to
compare couples of networks (homeomorphism...), but these methods do focus on couple of
networks that represent the same kind of information, like the network of TRI in E.coli
compared to equivalent networks in other organisms and that do not handle complementary
information.
In this Letter, we define a simple framework to study such complementarity in heterogeneous
networks only by their topology. The cooperativity of the proteins interactions upstream and
downstream the transcriptional network is very important in the understanding of regulatory
networks. Analogously, take into account the graph of transport airlines is fundamental for a
full description of these networks.
Motivated by these observations, we undertake in this paper the statistical analysis of complex
networks whose edges have been assigned a given category (for example PPI or TRI) and
thus can be generally described in terms of heterogeneous networks. Working with two
typical examples of this kind of networks, we introduce some metrics that in a natural way
study both topologies of connections. These quantities provide a general characterization of
the heterogeneous statistical properties and identify alternative definitions of centrality, local
cohesiveness, affinity... By appropriate measurements it is also possible to exploit the
correlation between the two graphs studied together, unveiling the complex architecture
shown by real heterogeneous networks.
.
Complement of the yeast transcriptional regulation network with protein-protein interactions
S. Smidtas, P. Bourgine, F. Képès, V. Schachter
2003
In order to understand the functioning of organisms on the molecular level, we need to know the design
principles underlying the networks that sustain cellular functions. The availability of entire genome
sequences and of high-throughput capabilities to determine gene coexpression patterns has shifted the
research focus from the study of single proteins, small complexes or genes to that of the entire proteome.
Of particular and not equal importance are the genetic network, a set of genes that interact through
directed transcriptional regulation, and the protein-protein interaction nework. While these two different
networks have been studied largely separetely in Yeast, we study for the first time global and local
topological properties of the heterogeneous network. How Protein-protein interactions complete the
transcriptional regulation network. We present first a network model that sustains such interactions
and allows to study its global properties and search for "network motifs," patterns of interconnections
occurring in complex networks at numbers that are significantly higher or lower than those in randomized
networks or with interesting dynamical behaviour. We applied the method to Saccharomyces cerevisiae data
set. The complete network contains 6541 proteins, 9971 protein-protein interactions or complexes (PPI)
and 7455 transcriptional regulations interactions (TRI). Analysis of the network global structure shows
that PPI and TRI complete themself more than expected in term of graph distance measure between proteins.
Proteins interactions are organised in layers upstream of the genetic regulatory process. Downstream PPI
complement purely transcriptional motifs and allow to better understand their functions. At last, because
protein-protein interactions are fast compared to slow transcriptional process, we found many loops
including the two types of data and we show in an example how yeast can take advantage of the two different
characteristic times of the two types of interactions. The loop chosen as a proof of concept is the
galactose regulation process including Gal4, Gal3 and Gal80. Though it has been studied for years, we
discovered why Gal4 not phosphorylated allows initation of transcription but not maintain galactose
dependant genes. This is due to a feed back loop that makes the system to act like a derivator.
.
Public French Contributions
Modélisation du réseau de régulation transcriptionelle de la levure et étude de ses propriétés structurales (French)
2002 Aout, Hybrigenics FR - Institut Pasteur
S. Smidtas - Master Thesis
L'accumulation de données post-génomiques permet de commencer à appréhender globalement les mécanismes
cellulaires de certains organismes modèles. En particulier, plusieurs études à grande échelle tant sur le protéome
que sur le transcriptome de Saccharomyces cerevisiae
sur ses réseaux de régulation et d'interaction. Les premiers travaux d'analyse ont fourni des résultats théoriques
sur la structure topologique globale de ces réseaux. Toutefois pour appréhender réellement leur fonctionnement,
le découpage en sous-réseaux ayant des rôles de contrôle et de transmission d'information clairement identifiés
semble une étape indispensable.
L'objectif de notre travail est d'étudier les propriétés structurelles de la régulation transcriptionnelle de la levure,
à partir d'un réseau plus complet obtenu en intégrant des informations d'interactions entre facteur de
transcription et ADN avec d'autres données, notamment d'interactions protéine-protéine.
Cette étude nécessite la définition d'un modèle formel permettant la description de ce réseau et la constitution
d'une base constituée autour d'un modèle de données, intégrant les données nécessaires à sa construction. Ces
deux piliers doivent permettre d'aborder des analyses de propriétés structurelles de complexité croissante.
PDF - Institut Pasteur - Hybrigenics
How To Analyse Data from micro-array experiments : A Simple Tutorial - (French)
2001, Supelec FR
S. Smidtas
PDF - Centre de Génétique Moléculaire (CGM)
The origins of life - CPGE-TIPE - (French)
1999, Louis-le-Grand FR
S. Smidtas
PDF
Les émulsions alimentaires, Utilisation de la Lécithine: Exemple de la mayonnaise - CPGE-TIPE - (French)
1999, Louis-le-Grand FR
S. Smidtas
PDF
Conference, Posters
YIB: A Tool for Biological Network Motif Analysis - Demo
ISMB - ECCB 2004, July 31 - August 4, Glasgow UK
Serge Smidtas
The Yeast Interaction Browser is a tool for network motif analysis and exploration of cell biochemical
interactions networks. It is provided with yeast molecular interactions data:
Protein-Protein interactions, Transcriptional Regulation and Metabolic network.
The web interface provides an easy way to search for complex heterogeneous motifs,
paths and view statistics.
ISMB04 - url - pdf
Reconstruction of a Genome-scale Model of Acinetobascter ADP1 sp. Metabolism and Analysis of Phenotypic Profiles. - Poster
ISMB - ECCB 2004, July 31 - August 4, Glasgow UK
Durot M., Le Fevre F., Pinaud B., Kreimeyer A., Perret A., De Bernardinis V. Smidtas S. Weissenbach J., Schachter V.
, Genoscope / CNRG and CNRS UMR 8030, France;
2nd European Conference on Prokaryotic Genomes, Göttingen, GE, September 23-26 2005
Session:
Genomics of agriculturally and environmentally important prokaryotes
Poster
PROKAGEN 2005
Completion of the yeast transcriptional regulation network by protein-protein interactions - Poster
ISMB - ECCB 2004, July 31 - August 4, Glasgow UK
Serge Smidtas, Genoscope / CNRG and CNRS UMR 8030, France;
Paul Bourgine, CREA, Ecole Polytechnique, Fr;
Franà§ois Képès, ATelier Génomique Cognitive, CNRS UMR 8071, Genopole®, Fr ;
Vincent Schachter, Genoscope / CNRG and CNRS UMR 8030, Fr.
In contrast to most recent studies on regulatory or protein interaction networks in yeast,
we focus here on global and local structure of the heterogeneous protein-protein and
protein-dna network. We introduce a formal network representation, simple yet expressive
enough to allow for both structural analyses and qualitative dynamics analyses of the heterogeneous
Topological properties of the heterogeneous network Analysing the connectivity structure of
the network, we obtain the following results: - the component networks (protein-protein and
protein-dna) complement each other by shortening network distance between proteins more
than expected - three distinct layers of protein interactions upstream of the genetic
regulatory process can be identified, and are consistent with existing annotations -
network motif searches show that feedback loops that include ppi are significantly overrepresented
relatively to a random model. From topological to dynamical properties We show how our formal
network representation allows a simple translation from the connectivity structure of a motif
to a simple qualitative model of its dynamics, allowing characterization of its functional role.
Applying this process to the well studied galactose assimilation pathway allows us to
identify a regulatory control loop with a clear function in adapting the yeast galactose
response to environmental conditions.
ISMB04 - url - pdf - poster pdf
Completion of the yeast transcriptional regulation network by protein-protein interactions - Poster
ICSB 2004, October 9 - 13, Heidelberg GE
Serge Smidtas, Genoscope / CNRG and CNRS UMR 8030, France;
Paul Bourgine, CREA, Ecole Polytechnique, Fr;
Franà§ois Képès, ATelier Génomique Cognitive, CNRS UMR 8071, Genopole®, Fr ;
Vincent Schachter, Genoscope / CNRG and CNRS UMR 8030, Fr.
In contrast to most recent studies on regulatory or protein interaction networks in yeast,
we focus here on global and local structure of the heterogeneous protein-protein and
protein-dna network. We introduce a formal network representation, simple yet expressive
enough to allow for both structural analyses and qualitative dynamics analyses of the heterogeneous
Topological properties of the heterogeneous network Analysing the connectivity structure of
the network, we obtain the following results: - the component networks (protein-protein and
protein-dna) complement each other by shortening network distance between proteins more
than expected - three distinct layers of protein interactions upstream of the genetic
regulatory process can be identified, and are consistent with existing annotations -
network motif searches show that feedback loops that include ppi are significantly overrepresented
relatively to a random model. From topological to dynamical properties We show how our formal
network representation allows a simple translation from the connectivity structure of a motif
to a simple qualitative model of its dynamics, allowing characterization of its functional role.
Applying this process to the well studied galactose assimilation pathway allows us to
identify a regulatory control loop with a clear function in adapting the yeast galactose
response to environmental conditions.
ICSB - url - pdf - poster pdf
ARC CPBIO
2002-06-02, Hybrigenics FR
Exposé sur une modélisation de réseau de régulation adaptée à l'étude de propriétés structurales
Calculs de Processus et Biologie des Réseaux Moléculaires
Action de Recherche Coopérative INRIA
CPBIO - url - pdf
Complex Biological Networks: Gene Regulation and Protein Interaction
September 19th - October 8th 2005, EXYSTENCE Thematic Institute, Torino, It
Invited to the ISI Foundation, Villa Gualino
The traditional approach to molecular biology has been an inherently local one, collecting and examining
data on a single gene, a single protein, a single biochemical reaction at a time, or at most of a
small number of factors believed to contribute to one specific function. In the last decades, however,
biology experienced fundamental changes. Rapid and continuing progress of biotechnology has made
fundamental biological mechanisms experimentally accessible on a genome-wide scale. This "Age of
Genomics" is characterized by an unprecedented wealth of data.
The challenge to utilize this data and turn it into an enhanced understanding of biological systems
is, however, wide open. Global, systemic, or network perspectives are becoming increasingly
important. Only a highly integrated level of investigation can hope to be able to address the
richness of phenomena observed on the molecular, on the cellular as well as on the organism scale.
ISI - Exystence
Software
Biological Interaction Browser
Online
The Yeast Interaction Browser is a tool for network motif analysis and exploration of cell
biochemical interactions networks. It is provided with yeast molecular interactions data:
Protein-Protein interactions, Transcriptional Regulation and Metabolic network. The web
interface provides an easy way to search for complex heterogeneous motifs, paths and view statistics.
BIB access
CyClone : a Java API to Biocyc
Le Fevre F., Smidtas S.
Adapting a modular and object-oriented approach in the design of biological modeling packages may reduce the software development barrier between ideas and their programmed applications. One big challenge is to build a library that will be accepted largely by the community. Towards this goal we developed Cyclone, a new object oriented pathway and genetic suite written in Java. Cyclone provides a comprehensive library of classes inspired by BioCyc that is the main pathway tool used and available by the community. Cyclone can open and save BioCyc files.
We present here Cyclone, a new pathway and genetic modeling package, which is built around one concept 'bioinformaticians' first.
Somewhat selfishly, we believe that the most precious resource in systems biology modeling is the bioinformatician development time.
We believe that these goals may be most easily achieved with object-oriented design.
The current set of classes in Cyclone is very much inspired by Biocyc, reflecting the most fill full systems biology database with more than 160 organisms, including metabolic pathways, regulatory networks and chemistry.
Cyclone on sourceforge - PPT - Cyclone Miror
Bi Graph Analysis Online Tool
An online tool to analyse a couple of graphs.
This tool study correlations and interactions between a couple of graphs. It implements the Graph Shuffle and Graph Rooting algorithms. The online version is limited to graphs smaller than 50 nodes/edges. Algorithm available upon request.
Bigraph online application
Journal Club
Biobricks MIT - PPT
2004-06-02, Evry FR
The development of well-specified, standard, and interchangable biological parts is a critical
step towards the design and construction of integrated biological systems. The MIT Registry
of Standard Biological Parts supports this goal by recording and indexing biological parts
that are currently being built and offering synthesis and assembly services to construct
new parts, devices, and systems.
url - ppt pdf
Motifs and feed-forward
2004-02-06, Evry FR
Structure and function of the feed-forward loop network motif
The Coherent Feedforward Loop Serves as a Sign-sensitive Delay Element in Transcription Networks
Mangan, Zaslaver Alon
Oct, Nov 2003 PNAS&JMB
url - ppt pdf
Biological computing, a brief history and tutorial
2003-07-11, Evry FR
"we learned more about how birds fly from trying to build airplanes than from studying structural anatomy of birds"
"A scientist discovers that which exists. An Engineer creates that which never was" Theodore von Karman
url - mov
Organization
CMSB 2004
2004 May 26-28, Paris FR
Computational Methods in Systems Biology '04
CMSB04 - url - archive pdf
Biopathways (ISMB SIG) 2004
2004-06-02, Glasgow UK
Biopathways -
Biopathways 2004 -
pdf -
archive pdf
