Archived Content

Cancer Informatics 

Final Agenda

TUESDAY, APRIL 24

7:00 am Workshop Registration and Morning Coffee

8:00 am - 4:00 pm Pre-Conference Workshops*

  • Software Development for Clinical Genomics
  • Microscopy Imaging Analysis – Quantitative Analysis of Large-Scale Biological Image Data

*Separate Registration Required

2:00 - 7:00 pm Main Conference Registration

4:00 Event Chairperson's Opening Remarks

Cindy Crowninshield, RD, LDN, Conference Director, Cambridge Healthtech Institute

4:05 Keynote Introduction

Sanjay Joshi, Solutions Architect, Life Sciences, EMC Isilon Storage Division

 

4:15 PLENARY KEYNOTES 

Martin LeachMartin Leach, Ph.D., CIO, Broad Institute of MIT and Harvard

 

Jill MesirovJill P. Mesirov, Ph.D., Associate Director and Chief Informatics Officer; Director, Computational Biology and Bioinformatics, Broad Institute of MIT and Harvard

 


Hitachi Data Systems5:00 - 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing

Drop off a business card at the CHI Sales booth for a chance to win 1 of 2 iPod touches® or 1 of 2 Xbox 360s®*!

*Apple® is not a sponsor or participant in this program

 

 

WEDNESDAY, APRIL 25

7:00 am Registration and Morning Coffee

7:55 Chairperson's Opening Remarks

Phillips Kuhl, Co-Founder and President, Cambridge Healthtech Institute

8:00 Keynote Introduction

Bas Burger, President, Global Commerce, BT Global Services

 

8:15 PLENARY KEYNOTE 

Eric PerakslisEric D. Perakslis, Ph.D., CIO and Chief Scientist of Informatics, U.S. Food and Drug Administration

 

8:45 Benjamin Franklin Award & Laureate Presentation

9:10 Best Practices Award Program

Cycle Computing small9:45 Coffee Break in the Exhibit Hall with Poster Viewing

 

DATA MODELING AND COMPUTATIONAL INTEGRATIVE TOOLS 

10:50 Chairperson's Remarks

William O'Neill, Ph.D., Professor, Bioengineering, University of Illinois at Chicago

11:00 Translational Integrity and Continuity: Individualized Biomedical Data Integration

Xiaoming Wang, Ph.D. Fellow, Computation Institute, University of Chicago and Argonne National Laboratory

This presentation describes an established warehousing system, translational data marts (TraM), to describe the impact of conceptual modeling on the system flexibility, sustainability, and scalability; data integration workflow efficiency; application capacity and performance; and data integrity and interoperability. An oncology data mart (ONCOD) will be used as an example to illustrate a lifecycle of a data warehousing system design.

11:30 Computational Statistical Image Modeling for Lesion Diagnosis and Classification

William O'Neill, Ph.D., Professor, Bioengineering, University of Illinois at Chicago

This presentation describes a method of diagnosing and classifying lesions for cancer and cancer type using only universally available computational software. Multimodal images of brain, breast, and thyroid are modeled by partial difference equations estimated as generalized least squares realizations. Model parameters afford individual lesion statistical diagnosis while Fisher linear discriminants optimally classify models of demographic populations.

BGI12:00 pm Gene Expression Quantification and Variation Detection from RNA-Seq data

Zhiyu Peng, Ph.D., Vice President of Bioinformatics Center, BGI

In order to better quantify the gene expression levels, BGI is now participating in the Sequencing Quality Control (SEQC) Project launched by the U.S. Food and Drug Administration (FDA), the goal of which is to demonstrate the utility of RNA-Seq technology and further establish standard and develop better algorithm for RNA-Seq quantification analysis. This talk will introduce two softwares, SOAPsplice and SOAPfusion.

 

BioFortis - small logo12:30 Luncheon Presentation: Enabling Scientific Discovery While Iteratively Cleaning and Standardizing Complex Clinical and Research Data

Matthew Clark, Ph.D., Senior Application Scientist, BioFortis, Inc.

Today's researchers have access to an ever-expanding treasure trove of electronic data. Traditionally, datasets must be cleaned and standardized before meaningful query and analysis can yield scientific insights. Large scale data cleaning efforts rarely meet desired objectives in time and on budget, delaying scientific discovery. This presentation will describe a new paradigm that allows cross-functional teams to collaboratively diagnose, repair, and circumvent data problems while delivering scientific value every step of the way.

1:40 Chairperson's Remarks

Michael Liebman, Ph.D., President & Managing Director, Strategic Medicine, Inc.

Sabrina Molinaro, Ph.D., Head, Epidemiology and Health Research Services, National Research Council of Italy

1:45 Personalized Medicine: Moving from Correlation to Causality in Breast Cancer

Michael Liebman, Ph.D., President & Managing Director, Strategic Medicine, Inc.

Sabrina Molinaro, Ph.D., Head, Epidemiology and Health Research Services, National Research Council of Italy

Co-authored with Valentina Lorenzoni, Stefania Pieroni, and Fabio Mariani, Unit of Epidemiology and Biostatistics, Institute for Clinical Physiology, National Research Council (Italy)

We have developed a fundamental model of the disease process for breast cancer, from pre-disease through early detection, treatment and outcome, and apply a multi-scalar approach across the risk assessment-enhanced diagnosis-therapeutic decision axis and will present the modeling methodologies. We believe this approach will improve clinical decisions and also drive enhanced development of diagnostics and therapeutic interventions.

Gene Expression Data Analysis 

2:15 The Allen Mouse Brain Atlas: Towards an Infrastructure for Neuroscience Data

Chinh Dang, Senior Director, Technology, Allen Institute for Brain Science

Launched in 2003, the Allen Mouse Brain Atlas contains genome-wide cellular level gene expression data in the adult mouse brain. Since then, additional gene expression atlases of the developing mouse brain, mouse spinal cord, adult human brain, developing human brain, and non-human primate brain are freely and publicly available with associated visualization and mining tools. Learn how this data can be leveraged by the genomic, bioinformatics, and other research communities.

Teradata2:45 Teradata Drug Discovery Analytics FrameworkEd Acker, Ph.D., Vice President, Life Sciences, TeradataThe Teradata Drug Discovery Analytics Framework removes data analysis barriers to drug discovery analytics. The barriers include data volume limits, data access limits(semantic, structural,location), data analysis limits (segmentation, aggregation) and analysis performance limits (data movement, application architecture). The major components of this framework are a 3NF Logical Data Model, a Massively Parallel Processing Share Nothing Data Management Architecture, in-database analytics for structured and unstructured data, a SQL interface for unstructured data and shareable virtual data labs self-provisioned by scientists.

Elsevier small logo3:00 Sponsored Presentation 



3:15 Refreshment Break in the Exhibit Hall with Poster Viewing 

3:45 Statistical Issues in the Analysis of Genome-Wide Methylation Arrays as Compared to Gene Expression Data: A Breast Cancer Example

Sandeep Singhal, Bioinformatician, Breast Cancer Translational Research Laboratory J.C. Heuson (BCTL), Jules Bordet Institute

This presentation will highlight some statistical methods for genome wide methylation data analysis with an emphasis on what new information is gained from breast cancer studies for which both DNA methylation and gene expression data is available and what conclusions can be reached about the role of DNA methylation on gene expression.

Molecular Profiling Data 

4:15 'Omics Interpretation Solutions - A Big Pharma Practical Guide

Jack Pollard, Ph.D., Associate Director, sanofi Oncology, Translational & Experimental Medicine – Bioinformatics

Lars Greiffenberg, Ph.D, sanofi R&D-IS, Health-IT, Biology Solutions

While generating testable hypotheses from 'omics data offers one kind of challenge, implementing informatics solutions company-wide presents a different set of technology, people and process challenges. We will share our recent successful experience and practical insights at specifying and implementing an integrated solution for 'omics data management, analysis, and interpretation for sanofi R&D.

4:45 GenomeSpace: An Environment for Frictionless Bioinformatics

Michael Reich, Director, Cancer Informatics, Broad Institute of MIT and Harvard

5:15 Best of Show Awards Reception in the Exhibit Hall

6:15 Exhibit Hall Closes

 

THURSDAY, APRIL 26

 

WEB-BASED PLATFORMS FOR SYSTEMS MEDICINE 

8:40 Chairperson's Opening Remarks

8:45 G-DOC: A Systems Medicine Platform for Personalized Oncology

Subha Madhavan, Ph.D., Director, Clinical Research Informatics, Lombardi Comprehensive Cancer Center; Director, Biomedical Informatics, Georgetown-Howard Universities CTSA, Georgetown University Medical Center

The Georgetown Database of Cancer (G-DOC) is a generic and flexible web-based platform that serves to enable basic, translational, and clinical research activities by integrating patient characteristics and clinical outcome data with a variety of high throughput research data in a unified environment. Through this modular, extensible, and flexible infrastructure, we can quickly and easily assemble new translational web applications with both analytic and generic administrative features.

9:15 Data Integration around Hierarchically and Modularly Organized Protein-Protein Interaction Network

Bing Zhang, Ph.D., Assistant Professor, Department of Biomedical Informatics, Vanderbilt University School of Medicine

Traditional graph-based network visualization techniques quickly become inadequate as network size and data complexity increase. We propose NetGestalt, a novel web-based data integration framework that exploits the inherent hierarchical modular architecture of protein-protein interaction networks to achieve high scalability. Using multidimensional cancer omics, as an example, we show that Netgestalt allows simultaneous presentation of large scale experimental and annotation data from various sources.

9:45 A Systems Approach to Designing Effective Clinical Trials

Vincent Fusaro, Ph.D., Research Associate, Center for Biomedical Informatics, Harvard Medical School

Randomized clinical trials are unsustainable in the era of personalized medicine due to the exponential number of combinations necessary for evaluating personalized treatment options. Computational methods are necessary to predict the likely outcomes and guide clinical trial designs.

10:15 Coffee Break in the Exhibit Hall and Poster Competition

10:45 Plenary Keynote Panel Chairperson's Remarks

Kevin Davies, Ph.D., Editor-in-Chief, Bio-IT World

10:50 Plenary Keynote Panel Introduction

Geoffrey Noer, Senior Director, Product Marketing, Panasas

 

11:00 Plenary Keynote Panel:
A special plenary session featuring trends and challenges in cancer research:
 

Julian Adams, Ph.D., President, Research and Development, Infinity Pharmaceuticals, Inc.

Jose Baselga, M.D., Ph.D., Chief and Bruce A. Chabner Chair, Division of Hematology/Oncology, Massachusetts General Hospital; Associate Director, Massachusetts General Hospital Cancer Center; Professor of Medicine, Harvard Medical School

Sir John Burn, MD, FMedSci, Professor of Clinical Genetics, Institute of Genetic Medicine, Newcastle University, UK; Genetics Lead, National Institute of Health Research, UK; Medical Director, QuantuMDx Ltd

John Quackenbush, Ph.D., Professor, Biostatistics and Computational Biology, Cancer Biology Center for Cancer Computational Biology, Dana-Farber Cancer Institute

12:15 Luncheon in the Exhibit Hall with Poster Viewing


MultipleX Assay Accuracy and Test Result Interpretation
 

1:55 Chairperson's Remarks

2:00 Personalized Patient Care through the Use of Multi-Biomarker Diagnostics and Novel Software Applications

Alex Bangs, CIO, Crescendo Bioscience, Inc.

A multi-biomarker blood test has been developed to more comprehensively measure disease activity in RA patients, and provide an objective, quantitative complement to traditional patient and physician assessments. These efforts are complemented by tools that enable physicians to track disease trajectory over time and take a more quantitative and personalized approach to patient care.

2:30 Comparing RNASeq Algorithms for Blood Gene Expression

Stan Letovsky, Ph.D., Vice President and CIO, SynapDx Corporation

Different expression quantitation algorithms for RNASeq data can give suprisingly different results. Here we report on comparisons of several algorithms run on the same dataset. We describe the impact of algorithmic choices on reproducibility and sensitivity to detect expression changes.

3:00 Accelerated Development of Diagnostic Assays Using NGENix™ in silico Powered Design

Richard Del Mastro, Vice President, Research and Development, IntelligentMDx

IMDx's proprietary NGENix™ bioinformatics platform powers the design process to rapidly develop qualitative and quantitative multiplexed real time PCR-based solutions to detect all strains of pathogens. NGENix™ utilizes modules that identify unique regions within sequenced genomes, designs oligonucleotide solutions, assesses the thermodynamics of the DNA multiplex and reviews cross-reactivity to other genomes. The process is efficient at generating accurate diagnostic assays with continued clinical relevancy.

3:30 Cloud-Based Development of Molecular Diagnostics Tests for Cancer

Ljubomir Buturovic, Ph.D., Vice President and Chief Scientist,Informatics, Pathwork Diagnostics, Inc.

Development of maximally informative genomics-based cancer diagnostics tests can present informatics challenges due to conceptual and computational complexity of analyzing the highdimensional genomics data. Pathwork Diagnostics developed a cloud-based software solution to this problem. The system had been used to develop informatics for the FDA-cleared Tissue of Origin cancer classification test currently marketed for clinical use, and can be applied to other prognostic and predictive diagnostic tests.

4:00 Conference Adjourns

 

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