Transcript Differential display analysis of alteration in gene expression

9th International Conference on
Intelligent System for Molecular
Biology
Tivoli Gardens, Copenhagen, Denmark
July 19-26, 2001
Park, Ji-Yoon
Satellite Meetings(July 19-20)
July 19
- The Open Source author’s contract : Steven Brenner
- BioJava project report: Thomas Down and Matthew Pocock
- Biopython project report: Andrew Dalke
- BioCORBA project report: Jason Stajich
- biok: Catherine Letondal
- Lightning Talks:
• OMG’s new Model Driven Architecture(MDA): Scott Markel
• BioRuby: Yoshinori Okuju, Toshiaki Katayama, and Mitsuteru Nakao
• Genquire: David Block
• Generation and use of substitution matrices in Biopython: IDDo Friedberg
and Brad Chapman
Satellite Meetings(July 19-20)
July 20
: Biopathway
- Bioperl project report: Hilmar Lapp
- EnsEMBL project report: Arne Stabenau
- Lightning Talks:
• Bioperl-project: Ewan Birney
• OpenBSA: Juha Muilu, Martin Senger and Alan Robinson
• Genetic algorithm and neural network libraries: Brad Chapman
• Mining gene expression information using a controlled hierarchical vocabulary
: Peter van heusden
• TFBS: Perl modules for transcription factor detection and analysis: Boris Lenhard
- A tool suite for the Gene Ontology: Chris Mungall, Hohn Richter, Bradley Marshall, and
Suzanna Lewis
- DeCAL: A system for constructing comparative maps: Debra Goldberg, Jon Kleinberg, and
Susan McCouch
Tutorial( July 21)
* Morning Turorials: Sat July 21 8:30-12:30
[Statistical analysis of micro-arrays studies]
: Emmanuel Lazaridis, University of South Florida
Afternoon Turorials: Sat July 21 14:00-18:00
[Network genomics]
: Christian Forst, Los Alamos National Laboratory
Sequence motifs, alignments and families:
July 22
[Keynote: Protein folding, molecular evolution, and human disease]
: Christopher M. Dobson, University of Oxford
►Protein misfolding in disease
►misfolded polypeptide
→
folded protein
↓
↓
misfolding
↓
↓
improper trafficking
toxic folding
degradation
►Asp67His: Amyloid formation(; aggregation)
►SH3 domain of
PI3 kinase: Cross- structure
Sequence motifs, alignments and families:
July 22
* An insight into domain combinations
* Prediction of the coupling specificity of G protein coupled
receptors to their G proteins
* Improved prediction of the number of residue contacts in
proteins by recurrent neural networks
* Non-symmetric score matrices and the detection of homologous
transmembrane proteins
* Generating protein interaction maps from incomplete data:
application to fold assignment
Sequence motifs, alignments and families:
July 22
[Keynote - Structural Genomics]
- Christopher M. Dobson, University of Oxford
- Goal : All protein domains carry all functional families
How many experimental structure?
- Coordination of international programs in structural genomics
- Pathways in expression profile
* 0j-py: a software tool for low complexity proteins and protein domains
: Michael J. Wise, Centre for Communications Systems Research
→ new tool for looking peptide
* Separating real motifs from their artifacts
* Feature selection for DNA methylation based cancer classification
* An algorithm for finding signals of unknown length in DNA sequences
Networks and Modeling: July 23
[Keynote- Protein Interactions]
: David Eisenberg, University of California, LosAngeles
• Rossetta Stone
- Fusion of functionally-linked domain
- http:// dip.doe-mbi.ucla.edu
• Phylogenic profile
- correlated occurrence of pairs of proteins in genomes
• Gene function
• Database interacting protein
• 3D domain swapping
• Signaling path
Networks and Modeling: July 23
<Protein-protein interaction map inference using interacting domain
profile pairs>
: Jerome Wojcik, Vincent Schachter, Hybrigenics S.A
► Computational prediction of protein network
► IDPP(Interacting domain profile pair) method
• Interacting domain cluster = vertics
• Interacting domain profile pair = edge
►Assessment of predictive accuracy: reference data problem
* Inferring subnetworks from perturbed expression profiles
: http:// www.cs.huji.ac.il/labs/combio
* Molecular classification of multiple tumor types
: http:// geone.wi.mit.edu/MPR
* Centralization: a new method for the normalization of gene expression data
Networks and Modeling: July 23
[ Centralization: a new method for the normalization of gene expression data ]
* Housekeeping approach is questionable.
* Basic assumption
; roughly the gene level expression no preffered direct of regulation
- real data: differently & strongly regulation
- total RNA vary: different cell state/tissue
- different factors are summed
- only subset of all gene measured
- strongly expressed gene be regulated: main protein product
* Advantage
- more robus on real data
- inexpensive alternative experiment
- Easy
Keynote- The phenomenon of the web: David Eisenberg, University of
California, Los Angeles
Networks and Modeling: July 23
[Keynote- The phenomenon of the web]
: David Eisenberg, University of California, Los Angeles
http: // rana.lbl.gov
http:// genome-www.standford. edu./microarray
Gene structure, Regulation, and
Modeling: July 24
* Keynote- The Modern RNA world: many genes don’t encode proteins
: Sean Eddy, Washington University
* Promoter prediction in the human genome
* Joint modeling of DNA sequence and physical properties to improve
eukaryotic promoter recognition
* Computational expansion of genetic networks
* GENIES: a natural-language processing systems for the extraction of
molecular pathways from journal articles
* Designing better phages
* Computational Analysis of RNA splicing
* Disambiguating proteins, genes, and RNA in text: a machine learning
approach
* Gene recognition based on DAG shortest paths
* An efficient algorithm for finding short approximate non-tandem
repeats
Methods: July 25
* Keynote- Membrane proteins: From the computer to the bench and
back: Gunnar von Heijne, Stockholm University
* Design of a compartmentalized shotgun assembler for the human
genome
* Probabilistic approaches to the use of higher order clone
relationships in physical map assembly:
* Fragment assembly with double-barreled data
* SCOPE: a probabilistic model for scoring tandem mass spectra
against a peptide database
* Probe selection algorithms with applications in the analysis of
microbial communities
* Fast optimal leaf ordering for hierarchical clustering
* Separation of samples into their constituents using gene expression
data
WEB: July 26
* Education in Bioinformatics: Current Trends and Issues.
- Shoba Ranganathan
* Opening Addresss: Bioinformatics Education
- Looking to the Future: Russ Altman
* The S* Life Science Informatics Alliance
- Shoba Ranganathan
* Bioinformatics BS at the Univerisity of California, Santa Cruz
- Kevin Karplus
* A Masters Degree in Bioinformatics in Switzerland
- Patricia Palagi
* Emerging US & UK Standards for Graduate Bioinformatics training
- Linda Ellis
WEB: July 26
* Bioinformatics Course Delivery: Tools and Infrastructure. Siv
Andersson(Chair)
* Bioinformatics: Introducing the concept of “ evaluation-based”
learning : Siv Andersson
* Problem-oriented sequence analysis tool: Ueng-Cheng Yang
* EMBER- A European Multimedia Bioinformatics Educational
Resource: C. Victor Jongeneel
* Virtual Reality and Visualization for Bioinformatics Education: YY
Cai
* Starting a new Bioinformatics Program. Phyllis Gardner(Chair)
* Initiating a multi-disciplinary, trans-institutional program: A Dean’s
perspective: Phyllis Gardner
* Insights into starting a new Multi-disciplinary program: Betty
Cheng
WEB: July 26
* Bioinformatics Training. Frederique Galisson(Chair)
* The Canadian Bioinformatics Workshops: Stephen Herst
* The BioNavigator Education Package- resources for practical
instruction in bioinformatics: Bruno A. Gaeta
* The Human Genome Mapping Project Resources CentreEncouraging Bioinformatics Awareness: Lisa Mullan
* Panel Discussion: Betty Cheng(Chair)
The S* Life Science Informatics Alliance: Question Time: S* Team
* Concluding Session: Closing Remarks. Shoba Ranganathan(Chair)
Bioinformatics Education: Future trends and perspectives: Philip
Bourne
Free Energy( ∆ G )
Thermodynamic constant that gives the amount of energy required
for or released by a reaction
- kcal/mol
- Reaction that require energy ; positive
- Reation that release free energy ; negative
- Energy must be released overall to form a base-paired structure
- The stability of the structure is determined by the amount of
energy released
Hairpin Structure
The Overall Free Energy of a doublestranded structure
∆ G total = ∆ G i + ∑ ∆ Gx + ∆ ∑ Gu
∆ Gi : the free energy for initiation of a double helix
 Positive value: + 3.4 kcal/mol
 It applied to intermolecular duplex formation
∑ ∆ Gx: the sum of the individual reactions involved in propagating the
double helix as each base pair is added
 the formation of each base pair releases energy ; negative
∑∆Gu: the sum of individual instances encountered as the double helix is
propagated in which the opposing bases are not complementary
 the energy required to hold these bases in an unpaired state
; positive
The Free Energy of formation for a
potential base-paired region
Free Energy of Base Pairing