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A C2B2 Activity!. A Systems and Structural Biology approach to the dissection of complex biological phenotypes. Perhaps surprisingly, a concise definition of systems biology that most of us Can agree upon has yet to emerge. ( Ruedi Aebersold, Faculty Member ISB ). MAGNet: Organization.

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A Systems and Structural Biology approach to the dissection of complex biological phenotypes

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A c2b2 activity

A C2B2 Activity!

A Systems and Structural Biology approach to the dissection of complex biological phenotypes

Perhaps surprisingly, a concise definition of systems biology that most of us

Can agree upon has yet to emerge. (Ruedi Aebersold, Faculty Member ISB)


Magnet organization

MAGNet: Organization

Contacted Alfonso Valencia, Dafne Koller, and Soren Brunak to join the SAB


Magnet mission

MAGNet Mission

  • To study the organization of the complex networks of biochemical interactions whose concerted activity determines cellular processes at increasing levels of granularity.

  • To provide an integrative computational framework to organize molecular interactions in the cell into manageable context dependent components.

  • To develop interoperable computational models and tools that can leverage such a map of cellular interactions to elucidate important biological processes and to address a variety of biomedical applications.


Magnet projects

MAGNet Projects

  • CORE 1

    • Project 1: Machine Learning

    • Project 2: Intermediating Models for Natural Language Processing and Ontology

    • Project 3: Meta-Ontologies for Bioinformatics Component Interoperability

    • Project 4: Novel Tools for Integration of Biological Database and Analyses

    • Project 5: GenAtomy: Algorithmic Approaches for the Integration of Genetic Variation and Expression Data in the Study of Regulation

  • CORE 2

    • Project 1: Sequence and Structure Based Annotation of Protein Interactions

    • Project 2: Reverse Engineering Gene Regulatory Networks from Genomic Data

    • Project 3: Sharing, Querying, Filtering, and Classifying Heterogeneous Phenoypes

    • Project 4: geWorkbench

  • CORE 3

    • Project 1: Structural and Energetic Basis of Cadhering Binding Specficity

    • Project 2: Regulatory Modules in Normal and Transformed B Cells

    • Project 3: Genetic Determinants of Common Heritable Disorders

    • Project 4: Understanding and Predicting Transcription Factor Specificity


A systems and structural biology approach to the dissection of complex biological phenotypes

Developmental

<>

Generating High-Throughput Data

Reverse Engineering the Networks

Genomic

Literature

Protein-Protein Complexes

Transcriptional

Signaling

Mol. Profiles

Structure

The Evolution of Systems Biology

Understanding Cell Physiology / Disease

Modeling Complexity

Evolution

Disease Models

Topology

Physiologic / Pathologic

Phenotype Regulation

Dynamics

Regulatory Network: Mesenchymal Signature of High-grade Glioma


Dissecting molecular interaction networks

Identification of Transcription Factor (TF) targets

Identification of Protein-Protein Interactions in Complexes

Identification of post-translational TF modifiers (Kinases, …)

Identification of post-transcriptional TF modifiers (miRs)

Polymorphysms’ role in molecular interactions

Can it be done computationally from high-throughput data?

Can it be done accurately?

Can it be biochemically/biologically validated?

Complex

P

P

Kinase

M

RNA

Degradation

Target 2

Target 3

Dissecting Molecular Interaction Networks

miR

RNA

RNA

P

Transcription

Factor

Target 1

Polymorphysms


Magnet algorithms

MAGNet Algorithms

  • Transcriptional Networks

    • ARACNe: Transcriptional Networks (Mammalian)

    • REDUCE: Transcriptional Networks (Yeast/Drosophila)

    • MEDUSA: Transcriptional Programs (Yeast/Drosophila)

  • Signaling/Co-factors/SNPs

    • MINDy: Signaling/co-factor Networks (Mammalian)

    • Genatomy: Transcription/Variability Networks (Yeast)

  • MicroRNA

    • Pipeline for the inference of microRNA from deep sequencing data

    • Inference of microRNA Regulatory Targets

  • Structure

    • MarkUs: Functional Annotation of Protein Surfaces

    • Skyline: Homology-based Structural Protein Models


Magnet algorithms1

MAGNet Algorithms

  • Interactome Assembly and Analysis

    • GeneWays: Literature Based, Integrated Interactomes

    • Mixed Bayesian Interactomes: Prot.-Prot./Prot.-DNA/microRNA-mRNA

      • B cells, Breast Cancer, Acute Myeloid Leukemia, Follicular Lymphoma, etc...

    • IDEA: Interactome Dysregulation Enrichment Analysis

      • Oncogenic Lesions, Drug/Biochemical Perturbations MOA

    • TIPhEn: Target Identification for Phenotypic Endpoint

  • Topological Properties

    • NetClass: Identification of Generative Models

    • InfoMod: Modularity Analysis

  • (Many others …)


Geworkbench genomic workbench

Integrated Genomics Platform

Support for gene expression data, sequences, pathways, structure, etc. (40+ visualization and analysis modules).

Access to local and remote data sources and analytical services.

Support for workflow scripting.

Integration with caGRID.

geWorkbench (genomic Workbench)

  • Based on caWorkbench, an NCI/caBIG-funded effort

  • Open source, Java based platform

Development framework

  • Open source development.

  • Modular/extensible architecture, supporting pluggable components with configurable user interface.

  • Formal (caBIG-registered) data models for multitude of bioinformatics concepts.

  • Easy integration of 3rd party components.


A platform for collaborative projects

A Platform for Collaborative Projects

  • DBPs:

    • The molecular basis of cell-cell adhesion (Cadherin specificity)

    • Dysregulated pathways in lymphomagenesis

    • Polymorphisms dysregulated pathways in neurodegenerative diseases (U.Chicago)

    • Combinatorial transcriptional regulation in early drosophila development.

  • Large Projects (Collaborative Projects RFA)

    • caBIG Knowledge Center for geWorkbench, caIntegrator, and GenePattern. (joint with Broad).

    • The Serious Adverse Event Consortium (SAEC)

    • Cancer Center P30: Excellent (Biomedical Informatics Shared Resource: Outstading)

  • Collaborative Projects

    • Genome wide Dissection of metabolic pathways (Los Alamos)

    • microRNA role in Prostate Cancer (MSK)

    • The molecular basis of addiction (Scripps) (R01 in funding range)

    • Minority Supplement (recommended for funding)

  • Others

    • Next-generation mouse models of prostate cancer progression and metastasis (submitted to the PCF), Systems-Based Dissection of Breast Cancer with Poor Prognosis (submitted to Avon), Master regulators of the Mesenchymal transformation of Glioblastoma Multiforme (R01 submitted), Transcriptional Networks determining stem cell differentiation (MSK), DLBCL Connectivity Map (BROAD), Methotraxate and PDX mechanism of action in T cell lymphoma (CC Pilot).


Magnet publications 07 08 45

MAGNet Publications 07/08 (45)

  • Jake M. Hofman, Chris H. Wiggins. A Bayesian Approach to Network Modularity. 2007. Submitted; URL

  • Lawrence David, Chris H. Wiggins. Benchmarking of Dynamic Bayesian Networks Inferred From Stochastic Time-Series Data. Annals of The New York Academy of Sciences, 2007. In press.

  • Etay Ziv, Ilya Nemenman, Chris H. Wiggins. Optimal Signal Processing in Small Stochastic Biochemical Networks. PLoS ONE, 2(10):e1077, Oct 2007. URL http://dx.doi.org/10.1371%2Fjournal.pone.0001077.

  • Kundaje A, …, Leslie C, and Zhang L. A predictive model of the oxygen and heme regulatory network in yeast. In review.

  • Kundaje A., …, Wiggins C, …, and Leslie C. Learning regulatory programs that accurately predict differential expression with MEDUSA. Annals of the New York Academy of Sciences, in press.

  • Christian Murphy, …, Gail Kaiser and Adam Cannon. Backstop: Debugging Tools for Novice Java Programmers. To appear in ACM SIGCSE Technical Symposium on Computer Science Education, March 2008.

  • Christian Murphy, Gail Kaiser and Marta Arias. Parameterizing Random Test Data According to Equivalence Classes. 2nd International Workshop on Random Testing, November 2007.

  • Rean Griffith, …, and Gail Kaiser. The Role of Reliability, Availability and Serviceability (RAS) Models in the Design and Evaluation of Self-Healing Systems. 3rd International Conference on Self-Organization and Autonomous Systems in Computing and Communications, September 2007

  • Rean Griffith, …, and Gail Kaiser. RAS Models: A Building Block for Self-Healing Benchmarks. 8th International Workshop on Performability Modeling of Computer and Communication Systems, September 2007.

  • Christian Murphy, Gail Kaiser and Marta Arias. An Approach to Software Testing of Machine Learning Applications. 19th International Conference on Software Engineering and Knowledge Engineering, July 2007.

  • StoyanovichJ et al., "EntityAuthority: Semantically Enriched Graph-Based Authority Propagation". Proceedings of the Tenth International Workshop on the Web and Databases (WebDB) June 2007.


Magnet publications continued

MAGNet Publications (continued)

  • Pe'erI and J Stoyanovich. "MutaGeneSys: Making Diagnostic Predictions Based on Genome-Wide Genotype Data in Association Studies", Columbia University technical report CUCS-012-07, 2007.

  • Ross KA et al. "A Faceted Query Engine Applied to Archaeology". Internet Archaeology 21, April 2007. Kenneth A. Ross and Julia Stoyanovich. "Schema Polynomials and Applications". Proceeding of the 11th International Conference on Extending Database Technology (to appear in March 2008).

  • Itsik Pe’er et al., “Estimation of the Multiple Testing Burden for Genomewide Association Studies of Nearly All Common Variants” Accepted Genetic Epidemiology.

  • Nair, R. and Rost, B. (2007) Predicting protein subcellular localization using intelligent systems. In Leon, D. and Markel, S. (eds), In Silico Technology in Drug Target Identification and Validation. Marcel Dekker.

  • Rost, B. (2007) Prediction of protein structure in 1D - Secondary structure, membrane regions, and solvent accessibility. In Bourne, P.E. and Weissig, H. (eds), Structural Bioinformatics - 2nd Edition. Wiley.

  • Schlessinger, …, and Rost, B. (2007) Natively unstructured loops differ from other loops, PLoS Comput Biol, 3, e140.

  • Schlessinger, …, and Rost, B. (2007) Natively unstructured regions in proteins identified from contact predictions, Bioinformatics, 23, 2376-2384.

  • Fasnacht, M., ... and Honig, B. (2007) Local Quality Assessment in Homology Models Using Statistical Potentials and Support Vector Machines. Prot. Sci. 6:1557-1568.

  • Boorsma, X, …, and H.J. Bussemaker. Inferring transcription factor co-modulation networks through regulon-based expression analysis. Proceedings of RECOMB Sattellite Meeting on Systems Biology, San Diego, CA, November 2007.

  • Stolovitzky GA, Monroe D, and Califano A (2007), Dialogue on Reverse Engineering Assessment and Methods: the DREAM of high throughput pathway inference, Ann NY Acad Sci. 2007 Oct 9.

  • Margolin AA, and Califano A (2007), Theory and limitations of genetic network inference from microarray data, Ann NY Acad Sci. 2007 Oct 9;


Magnet publications continued1

MAGNet Publications (continued)

  • Mani K, …, Dalla-Favera R, and Califano A, (2007) A Systems Biology Approach to the Prediction of Causal Oncogenic Mechanisms and Drug Mechanism-of-Action Profiles in Cancer Phenotypes, Molecular Systems Biology, in press.

  • Wang K, …, Dalla-Favera R, and Califano A, (2007), Genome-wide identification of transcriptional network modulators in human B cells, submitted to Nature.

  • Carro MS, …, Califano A*, Iavarone A* (2007), A transcriptional regulatory network initiates and maintains the mesenchymal phenotype of human malignant glioma, submitted to Science.

  • Margolin AA, …, Califano A*, and Stolovitzky G* (2007), ChIP-on-chip significance analysis reveals large scale transcription factor activity, submitted to Nature Biotechnology.

  • Lussier YA* and Bodenreider O*. Clinical Ontologies for Discovery Applications. P.101-119 Chritopher Baker and Kei Cheung, Editors. Semantic Web: Revolutionizing Knowledge Discovery in the Life Sciences. Springer Verlag 2007, XXII, 450 p.

  • Lussier YA. Ontology Similarity Networks and Database Interoperability. Interface 2007, May 23-26, Philadelphia.

  • Tao Y, Li J, Friedman C*, Lussier YA*. Information Theory Applied to the Sparse Gene Ontology Annotation Network to Predict Novel Gene Function. Bioinformatics, 2007, 23(13)i529-38.

  • Tao Y, Patel C, Friedman C, Lussier YA*. PIE: A Phenotype Interface Engine for Automated Representation in PATO and “Semantic Web”-Based Exchange of Clinical Data and Narratives. AMIA Annu Symp Proc. 2007 (in press).

  • Payne PRO, Lussier YA et al. Re-engineering Translational Research: Are We Taking A Truly Translational Approach? (Submitted to the AMIA Summit in Biomedical Informatics).

  • Liu Y, …, Lussier YA*. Robust Methods for Accurate Diagnosis Using Microbiological Arrays. (Submitted to the AMIA Summit in Biomedical Informatics).

  • Sam L. , …, Friedman C and Lussier YA*. PhenoGO: A Resource for Multiscale Biological Data Integration. (Submitted to the AMIA Summit in Biomedical Informatics).


Magnet publications continued2

MAGNet Publications (continued)

  • Ciatto, C., … , Honig, B. and Shapiro, L. Crystal structures and adhesive binding mechanism of T-cadherin. Structure, submitted.

  • Koehnke, J, …, Honig, B., …. and Shapiro, L., Crystal structures of the neureoligin-binding domains from neurexin 1 and neurexin 2. Structure, in press.

  • Koehnke, J,… , Honig, B. and Shapiro, L., Crystal structure of the ectodomain from Nlgn2. PNAS, in press.

  • Posy, S., Shapiro, L., and Honig, B., J. Mol. Biol, submitted.

  • J. Sebat, …, Gilliam TC, …, and M. Wigler (2007). Strong association of de novo copy number mutations with autism. Science, 316: 445-449.

  • Autism Genome Project Consortium. (2007). Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nat. Genet. 39: 319-328.

  • Ivan Iossifov, …, Gilliam TC and A Rzhetsky. Genetic-linkage mapping of complex hereditary disorders to a whole-genome molecular-interaction network. Submitted.

  • R.A. Kumar, …, Gilliam TC, et al. Discovery and Characterization of a Recurrent 6p11.2 Microdeletion Identified in 0.6% of Autism Patients. In review (Nature Genetics )

  • RA Kumar, …, Gilliam TC, et al. (2008). Recurrent 16p11.2 microdeletions in autism. Human Molecular Genetics, In press.

  • R Suresh, …, and Gilliam TC. Sex-specific interaction between ITGβ3 and SLC6A4 in Autism Spectrum Disorder. Submitted.

  • Wellcome Trust Case Control Consortium. (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661-678.

  • Rzhetsky A, et al.. (2007). Probing genetic overlap among complex human phenotypes. Proc Natl Acad Sci, 104, 11694.


Dbp renewal

DBP Renewal

  • 4 very high quality proposals

    • Riccardo Dalla-Favera and Andrea Califano: microRNA regulatory networks in human B cells.

    • Levi Garraway and Dana Pe'er: Therapeutic Opportunities in Melanomals

    • Antonio Iavarone and Andrea Califano: A transcriptional regulatory network for the mesenchymal phenotype in malignant gliomas.

    • Richard Losick and Dennis Vitkup: Computational and experimental analysis of bacterial developmental (sporulation) network.

  • Full proposals due on April 30th

  • Review and funding decision by Aug. 1st


The 4 th recomb conf on systems biology nov 2007

The 4th RECOMB Conf. on Systems Biology (Nov 2007)


The 2 nd dream meeting dec 2007

The 2ndDREAM Meeting (Dec. 2007)

http://www.nyas.org/ebriefreps/splash.asp?intEbriefID=705


2008 joint recomb systems biology and regulatory genomics meeting dream track

2008 Joint RECOMB Systems Biology and Regulatory Genomics Meeting (DREAM Track)

Martha Bulyk (RG), Andrea Califano (SB), Manolis Kellis (RG), Gustavo Stolovitzky (DR)

Sun Nov 2

1pm

Wed Oct 29

5pm


Venue mit broad institute csail

Venue: MIT / Broad Institute / CSAIL

Cambridge MA

Broad

Institute

CSAIL


And now the fun begins

And now the fun begins

  • We have created the infrastructure in Years 1-3

  • Over the next 7 years, we can concentrate on the science!

MAGNet


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