Bio IT World Expo 2016  
Bio IT World Expo 2016
2014 Archived Content


Track 4 explores technologies and tools that bring together relevant -omic data from multiple physical locations for analysis. Case studies and results will be presented to illustrate how virtual data integration across multiple research initiatives can be applied to any disease. Other topics covered include collaboration tools, biomarker research, imaging, computational models, clinically actionable variants, and gene mapping and expression.

Final Agenda

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7:00 am Workshop Registration and Morning Coffee

8:00 - 11:30 Recommended Morning Pre-Conference Workshops*

Data Visualization in Biology: From the Basics to Big Data
Analyzing NGS Data in Galaxy

12:30 - 4:00 pm Recommended Afternoon Pre-Conference Workshops*

Big Data Analytics
Running a Local Galaxy Instance

*Separate Registration Required. Click here for detailed information.

2:00 - 7:00 pm Main Conference Registration

4:00 Event Chairperson's Opening Remarks

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


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5:00 – 7:00 Welcome Reception in the Exhibit Hall with Poster Viewing




7:00 am Registration Open and Morning Coffee

8:00 Chairperson's Opening Remarks

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


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9:00 Benjamin Franklin Award & Laureate Presentation

9:30 Best Practices Awards Program

9:45 Coffee Break in the Exhibit Hall with Poster Viewing

Bioinformatics for Big Data 

10:50 Chairperson's Remarks
Les Mara, Founder, Databiology, Ltd. 

11:00 Data Management Best Practices for Genomics Service Providers

Vas Vasiliadis, Director, Products, Computation Institute, University of Chicago and Argonne National Laboratory

Genomics research teams in academia and industry are increasingly limited at all stages of their work by large and unwieldy datasets, poor integration between the computing facilities they use for analysis, and difficulty in sharing analysis results with their customers and collaborators. We will discuss issues with current approaches and describe emerging best practices for managing genomics data through its lifecycle.

11:30 NGS Analysis to Drug Discovery: Impact of High-Performance Computing in Life Sciences

Bhanu Rekepalli, Ph.D., Assistant Professor and Research Scientist, Joint Institute for Computational Sciences, The University of Tennessee, Oak Ridge National Laboratory

We are working with small-cluster-based applications most widely used by the scientific community on world's premier supercomputers such as Titan, Jaguar and Kraken. We incorporated these parallel applications into science gateways (PoPLAR: the Portal for Petascale Life sciences Applications and Research) with user-friendly, web-based portals. Learn how the research at UTK-ORNL will help to bridge the gap between the rate of big data generation in life sciences and the speed and ease at which biologists and pharmacists can study this data.

12:00 pm The Future of Biobank Informatics

Bruce Pharr, Vice President, Product Marketing, Laboratory Systems, Remedy Informatics

As biobanks become increasingly essential to basic, translational, and clinical research for genetic studies and personalized medicine, biobank informatics must address areas from biospecimen tracking, privacy protection, and quality management to pre-analytical and clinical collection/identification of study data elements. This presentation will examine specific requirements for third-generation biobanks and how biobank informatics will meet those requirements.

12:15 Learn How YarcData’s Graph Analytics Appliance Makes It Easy to Use Big Data in Life Sciences

Ted Slater, Senior Solutions Architect, Life Sciences, YarcData, a division of Cray

YarcData, a division of Cray, offers high performance solutions for big data graph analytics at scale, finally giving researchers the power to leverage all the data they need to stratify patients, discover new drug targets, accelerate NGS analysis, predict biomarkers, and better understand diseases and their treatments.

12:40 Luncheon Presentation I: Leveraging Enterprise Architecture to Drive Bioinformatics Solutions

Les Jordan, Director, Life Sciences IT Consulting, Quintiles

Session will discuss an approach to breaking down barriers to sharing information – focused on bioinformatics - and establishing priorities that can then be applied across the value chain.

1:10 Luncheon Presentation II (Sponsorship Opportunity Available) or Lunch on Your Own 

1:50 Chairperson's Remarks

Michael Liebman, Ph.D., Managing Director, IPQ Analytics, LLC

Sabrina Molinaro, Ph.D., Head of Epidemiology, Institute of Clinical Physiology, National Research Council - CNR Italy

1:55 Integration of Multi-Omic Data Using Linked Data Technologies

Aleksandar Milosavljevic, Ph.D., Professor, Human Genetics; Co-Director, Program in Structural & Computational Biology and Molecular Biophysics; Co-Director, Computational and Integrative Biomedical Research Center, Baylor College of Medicine

Increasing throughput of sequencing forces local data processing and fragmentation of data. Local data custody is also often required for regulatory (HIPAA, IRB) and business reasons. By virtue of programmatic interoperability (uniform REST APIs), Genboree servers enable virtual integration of multi-omic data that is distributed across multiple physical locations. Linked Data technologies of the Semantic Web provide an additional “logical” layer of integration by enabling distributed queries across the distributed data and by bringing multi-omic data into the context of pathways and other background knowledge required for data interpretation. We demonstrate how a combination of virtual and logical data integration opens new opportunities for data mining and discovery.

2:25 Building Open Source Semantic Web-Based Biomedical Content Repositories to Facilitate and Speed Up Discovery and Research

Bhanu Bahl, Ph.D., Director, Clinical and Translational Science Centre, Harvard Medical School

Douglas MacFadden, CIO, Harvard Catalyst at Harvard Medical School

Eagle-i open source network at Harvard provides a state-of-the-art informatics platform to support the quality control and annotation of resources establishing a sound foundation for a well-curated resource collection in accordance with Semantic Web and Linked Open Data principles. Learn how this ontology-centric architecture is used to efficiently store, create, and search data.   

2:55 Analysis of Disease and Drug Interactions in the Elderly: An Application of Big Data

Michael Liebman, Ph.D., Managing Director, IPQ Analytics, LLC

Sabrina Molinaro, Ph.D., Head of Epidemiology, Institute of Clinical Physiology, National Research Council - CNR Italy

Diagnosis and treatment in elderly patients presents a unique set of challenges because of their extensive clinical history, altered physiology and physiological response both to diseases and treatments, patterns of behavior and access to appropriate medical care. Although certain characteristics can be present in patients at any age, several are particularly prevalent among the elderly: active co-morbid conditions; extended history of taking multiple medications; utilization of multiple physicians/specialists without a single point of coordination of care; presentation of signs and symptoms that could result from undiagnosed disease, side-effects of current medications, interactions among current medications, failure to adhere to prescribing directions, cognitive decline and confusion which can lead to drug misuse/abuse, etc. This study highlights application of big data to address the complexity in treatment of elderly patients with diabetes and hypertension. 

3:25 Refreshment Break in the Exhibit Hall with Poster Viewing

Biological Networks 

4:00 Network Verification Challenge: A Reputation-Based Crowd-Sourced Peer Review Platform for Network Biology

William Hayes, Ph.D., Senior Vice President, Platform Development, IT/Informatics, Selventa

Anselmo DiFabio, Vice President, Technology, Applied Dynamic Solutions

The Network Verification Challenge proposes a new approach for peer review for Network biology. The use of a reputation-based crowd-sourced platform can make previously overwhelming efforts in capturing large-scale network biology and validating it possible. The same approach for peer review can also be applied inside bioPharma for internal collaboration and validation of network biology in and across therapeutic areas. We will describe a web application project we have developed and the role of crowd-sourced application.

4:30 NDEx, the Network Data Exchange: Bridging the Knowledge Gap for Commercial and Academic Collaboration on Biological Networks

Dexter Pratt, Project Director, NDEx, Cytoscape Consortium

NDEx is a public portal for collaboration and publication for scientists and organizations working with biological networks of multiple types and in multiple formats. This talk presents key features of the NDEx portal and the underlying open-source server software. We will show the facilities of the beta version of the NDEx portal, the use of the NDEx REST API via Cytoscape and other applications, and the coordination of private NDEx servers with the public portal. The status of NDEx in collaborations with other organizations and the use (or development) of standards will be summarized.

5:00 MINE: A Novel Computational Approach for Gene Network Identification
Diane Joseph-McCarthy, Ph.D., Vice President, Chemistry & Computational Science, EnBiotix, Inc. 

A perturbation to a biological system results in changes to molecular processes, signaling networks, and the constituent genes. These changes reflect the mode-of-action (MOA) of the perturbation and, if properly characterized, can be used to gain insights into how the perturbation acts. Our novel MINE approach (Mode-of-action by Iterative Network Expansion), leverages the strengths of two well-established computational methods: MNI (Mode-of-action by Network Identification) and CLR (Context Likelihood of Relatedness). MINE iteratively uses both methods to allow for enhanced characterization of the biological processes underlying a perturbation. Details of this approach as well as initial results in mammalian datasets will be presented.

5:30 - 6:30 Best of Show Awards Reception in the Exhibit Hall


7:00 am Registration Open

7:00 Breakfast Presentation (Sponsorship Opportunity Available) or Morning Coffee

8:00 Chairperson’s Opening Remarks

Kevin Davies, Ph.D., Vice President Business Development & Publisher C&EN, American Chemical Society; Founding Editor, Bio-IT World


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10:00 Coffee Break in the Exhibit Hall and Poster Competition Winners Announced

Bioinformatics across Multiple Research Initiatives 

10:30 Chairperson's Opening Remarks
Subha Madhavan, Ph.D., Director, Innovation Center for Biomedical Informatics, Oncology, Georgetown University 

10:35 Analysis of Genomics Data in an Internal Cloud Computing Environment

Philip Groth, Ph.D., IT Business Partner Genomics, R&D IT - Research, Bayer HealthCare

We have developed vCloud, an in-house cloud solution, which we have successfully deployed an analysis pipeline for Copy Number calculations and a recently published prediction algorithm for novel fusion proteins in cancer. This talk presents the technical set-up of vCloud, maintenance and running an internal cloud-computing environment, and how this set-up enables fast & secure analysis of large-scale genomics data. Results of analyzing genomic data from over 4,000 cancer patients will be presented.

11:05 Genome-Wide Multi-Omics Profiling of Colorectal Cancer Identifies Immune Determinants Strongly Associated with Relapse

Subha Madhavan, Ph.D., Director, Innovation Center for Biomedical Informatics, Oncology, Georgetown University

This presentation demonstrates the use of novel informatics methods and data integration approaches in identifying prognostic markers of cancer. The use and benefit of adjuvant chemotherapy to treat patients with state II colorectal cancer (CRC) is not well understood since the majority of these patients are cured by surgery alone. Identification of biological markers of relapse is a critical challenge to effectively target treatments to the ~20% of patients destined to relapse.

11:35 Bioinformatics Initiatives Spanning Academia, Biotech and Pharma
Gerry Higgins, M.D., Ph.D., Vice President, Pharmacogenomic Science, AssureRx Health, Inc. 

12:15 pm Luncheon Presentations (Sponsorship Opportunities Available) or Lunch on Your Own

1:15 Dessert Refreshment Break in the Exhibit Hall with Poster Viewing

1:55 Chairperson's Remarks
Simon Berkovich, Ph.D., Professor, Computer Science, The George Washington University 

2:00 An Algorithm to Access Human Memory Showing Alzheimer Symptoms When Distorted

Simon Berkovich, Ph.D., Professor, Computer Science, The George Washington University

This talk presents a novel theoretical framework for bioinformatics. Access to holographic model of the brain encounters a particular problem of multiple responses resolution. For the given milieu, we employ a digital-analog adjustment of a streaming algorithm for finding a predominant element. This construction markedly exhibits all well-recognized properties of human memory, including better remembrance of repeated items and earlier events. Receptacles deterioration incurs preferential recall of prior life stages akin to Alzheimer’s disease.

Machine Learning Models 

2:30 Accurate Prediction of Clinical Stroke Scales from Robotic Measurements

Dimitris K. Agrafiotis, Ph.D., FRSC, Vice President and Chief Data Officer, Covance

One of the greatest challenges in clinical trial design is dealing with the subjectivity and variability introduced by human raters when measuring clinical end-points. Here, we describe a novel approach that combines robotic devices and advanced machine learning algorithms to derive predictive models of clinical assessments of motor function following stroke. We show that it is possible to derive sensitive biomarkers of motor impairment using a few easily obtained robotic measurements, which can then be used to improve the efficiency and cost of clinical trials.

3:00 GPS Engineering: Machine Learning Approaches to Biological Engineering

Drew Regitsky, Scientist, Bioengineering, Calysta Energy

Maturation of biotechnology has reached a point where comprehensive, systematic approaches are becoming more practical and indeed necessary to fully realize the potential of engineered biological systems. This talk presents a potential new approach to computational representations of biological systems and applying multidimensional analysis to predicting the behavior of complex systems. Several case studies will be presented to demonstrate applications of the methods and examples of the output of data analysis.

3:30 A Multiclass Extreme-Learning-Machine Approach to the Discovery of Multiple Cancer Biomarkers: Using Binary Coded Genetic Algorithm and IPA Analysis

Saras Saraswathi, Ph.D., Clinical Instructor, Pediatrics, Ohio State University; Postdoctoral Research Associate, Battelle Center for Mathematical Medicine, Research Institute, Nationwide Children’s Hospital

The neural network based Extreme Learning Machine is combined with a Binary Coded Genetic Algorithm to select a small set of 92 genes which simultaneously classify 14 different types of cancers simultaneously, to high accuracy. IPA analysis of the selected genes reveals that over 60% of the selected genes are related to many cancers that are being classified. In addition, over 30 molecules related to these genes are identified as experimentally identified bio-markers related to prognosis, diagnosis and treatment of cancer.

4:00 Conference Adjourns


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  • Making the World's Knowledge Computable
  • Bioinformatics in the Cloud
  • The Application of Text Analytics to Drug Safety Surveillance

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