Mini Conference with Bindley Bioscience Center - Department of Statistics - Purdue University Skip to main content

Mini Conference with Bindley Bioscience Center


When: Friday, December 4, 2020, 10:30 a.m. – 12:00 p.m.

Speakers and Discussants: Ramaswamy Subramanian, Andrew Mesecar, Jean-Christophe Rochet, Bartek Rajwa, Michael Poderycki, Andy Schaber, Dennis Lin, Mark Daniel Ward, and Dabao Zhang, Purdue University

Where: Zoom (contact organizer Bingxin Zhao, Assistant Professor of Statistics, for link-- bingxin at purdue dot edu)

Bindley Bioscience Center ( is a life science hub for interdisciplinary research on Purdue's campus. As Purdue’s leading innovation research support facility, Bindley Bioscience Center provides a platform to integrate interdisciplinary life sciences research with engineering to create unique opportunities to solve global challenges in the life sciences. During this mini conference, researchers from the Bindley Bioscience Center will provide an overview of Bindley’s core facilities and showcase their key research areas with a few specific examples. This event will provide an opportunity to foster interdisciplinary collaborations between Purdue Statistics and Bindley Bioscience Center and enhance biological data science research at Purdue.


10:30-10:35 a.m.
Opening notes: Dennis Lin, Rams Subramanian

10:30-10:50 a.m.
Data science opportunities and challenges in phenotype "-omics" techniques. A view from Bindley Bioscience Center - link to abstract
Presenter: Bartek Rajwa

10:50-11:05 a.m.
Overview of the Purdue Center for Cancer Research: Computational efforts and programs
Presenter: Andrew Mesecar

11:05-11:15 a.m.
Toward a Bindley - Data Mine partnership - link to abstract
Presenter: Mark Daniel Ward

11:15-11:30 a.m.
Purdue Institute for Integrative Neuroscience: Strategic Initiatives Built on a Foundation of Data Science
Presenter: Chris Rochet

11:30 a.m.- 12:00 p.m.
Discussion and Q&A Section
Discussants: Rams Subramanian, Andy Schaber, Mike Poderycki, Dennis Lin, Dabao Zhang, Bingxin Zhao


Ramaswamy Subramanian
Director, Bindley Bioscience Center
Professor, Biological Sciences
Professor, Weldon School of Biomedical Engineering
Purdue University

Andrew Mesecar
Professor and Head, Department of Biochemistry
Walther Professor of Cancer Structural Biology
Deputy Director, Purdue Center for Cancer Research
Purdue University

Jean-Christophe (Chris) Rochet
Director of Purdue Institute for Integrative Neuroscience
Professor of Medicinal Chemistry and Molecular Pharmacology
Purdue University

Bartek Rajwa
Research Associate Professor
Purdue University

Michael (Mike) Poderycki
Team Lead, Research Innovation Acceleration, Bindley Bioscience Center
Purdue University

Andy Schaber
Imaging Facility Director, Bindley Bioscience Center
Purdue University

Dennis Lin
Professor and Head, Department of Statistics
Purdue University

Mark Daniel Ward
Professor of Statistics and (by courtesy) of Agricultural & Biological Engineering, Mathematics, and Public Health
Director of The Data Mine
Interim Co-Director of the Integrative Data Science Initiative Purdue University
Purdue University

Dabao Zhang
Associate Professor of Statistics
Purdue University

Bingxin Zhao
Assistant Professor of Statistics



Data science opportunities and challenges in phenotypic “-omics” techniques. A view from Bindley Bioscience Center. 

Presenter: Bartek Rajwa

Although the “-omics” suffix is typically associated with genomics, suggesting that processing genomic data is the most common task of modern bioinformatics, the rich landscape or research activities within proteomics, metabolomics, cytomics, microbiomics, connectomics, and beyond is linked mainly with phenotypic rather than genotypic information. These readouts do not possess a-priori known syntax and cannot be readily interpreted and understood unless curated, annotated by domain experts, then reduced, and visualized using various statistical and machine learning approaches. When paired with multifactorial experimental design, the phenotypic measurements employing mass spectroscopy, cytometry, automated microscopy, and other platforms produce massive datasets, internally organized as tensors that must be simplified and condensed to be utilized in any testable biological model. The interaction with such data becomes even more difficult if multiple techniques are used simultaneously with the expectation that the merged collection of features would provide more comprehensive knowledge regarding the researched biological system. Therefore, the organization and interpretation of biological phenotypic data bring several exciting and unique data science challenges. This presentation will briefly outline some fundamental data analysis and interpretation problems in platforms serving ‑omics research. A particular emphasis will be given to the issues of biological data fusion, predictive features extraction, phenotypic data reduction and visualization, as well as the experimental design of profiling and screening experiments.

Toward a Bindley - Data Mine partnership

Presenter: Mark Daniel Ward

Abstract:  The Data Mine is a campus-wide program for undergraduate and graduate students, from all colleges at Purdue.  It is intended to enable students to work in data-driven research projects on campus, and in Corporate Partners with mentors beyond Purdue.  In both cases, it is essential to have real-world problems and large, complex data sets that can be shared with students.  We hope to briefly discuss the potential to build a Bindley - Data Mine partnership for fall 2021 - spring 2022.

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