Challenges and Opportunities in Plant Science

Seung Yon (Sue) Rhee PhD

Nov 12, 2020|12:00 PM – 1:00 PM

Plants make up the biggest biotic component of the biosphere and play essential roles in all ecosystems. Our survival and well-being depend on plants and this dependence will increase as the climate changes rapidly. To improve how we obtain food, energy, and materials from plants and steward the health of our environment for future generations, we need to understand how plants work at multiple scales from molecules to cells to ecosystems. A major challenge to achieving this goal is a limited understanding of functions of plant genes. The majority of genes in plant genomes are uncharacterized and many of them are found only in plant lineages. Traditional sequence-similarity based biochemical function inference cannot address this challenge. Another aspect of gene function that is critical but generally lacking is the spatial and temporal context under which gene products operate. These challenges have, in part, driven the spectacular advances and inventions in genomics, imaging, mass spectrometry and we are now capable of high-throughput, high-content, and high-resolution measurements of gene and protein function parameters. Along with these technologies and emerging datasets, we need advances in computational biology and bioinformatics tools, concepts, and methods. In this talk, I will describe these challenges and some of the efforts we are making in addressing them.

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Perspective on Deep Imaging

Ge Wang PhD

Mar 05, 2020|12:00 PM – 1:00 PM

130 University Health Services Building (Pizza & drinks served at 11:50) Please RSVP to

Artificial intelligence is now recognized as an on-going paradigm shift, with an emphasis on machine learning especially deep learning. Computer vision and image analysis are two major applications of deep learning. While computer vision and image analysis deal with existing images and produce features of these images (images to features), tomographic imaging produces images of multi-dimensional structures from experimentally measured data (line integrals, harmonic components, and so on, of underlying images) which are tomographic features (features to images). Since 2016, deep learning is being actively developed worldwide for tomographic imaging, forming a new area of imaging research. In this presentation, we present a perspective on deep imaging involving data processing, image reconstruction, radiomics, and beyond. We show deeptomographic results and also explore network innovations.

Slides from presentations:

Perspective on Deep Imaging

Medical Imaging in the Deep Learning Framework

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Accelerating Bioinformatics Applications using GPUs

Fernanda Foertter PhD

Feb 20, 2020|12:00 PM – 1:00 PM

University Health Services 130 (pizza and drinks at 11:50 - RSVP to

The biological sciences are currently experiencing an increase in data size and complexity. Traditional methods are now reaching the point they can no longer keep up with the data output. Larger datasets, particularly when combined with other data sources, open opportunities to apply methods like deep learning on these complex data. NVIDIA is contributing to these needs by developing algorithms that can leverage graphics processing units (GPUs). These problems benefit from high memory bandwidth and very high parallelism inherent of the GPU architecture. This talk will explore some of the collaborations we have with industry and academia and share some of what our research team is currently working on.

GPUs for Genomics

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Promoting Transparency in Biomedical Publications Using Natural Language Processing

Halil Kilicoglu PhD

Feb 06, 2020|12:00 PM – 1:00 PM

130 University Health Services Building, Please RSVP to


Rigor, reproducibility, and transparency of biomedical research has been the topic of much debate in recent years. Some ongoing efforts aim to address the issues in research conduct and dissemination by focusing on standardization and guideline development. As biomedical research output increases exponentially, automated tools are needed to complement such efforts and assist the stakeholders (e.g., scientists, journals, funding organizations) in assessing and improving research output.

Textual artifacts (e.g., grant applications, study protocols, manuscripts, and publications) are central to biomedical communication. With the progress made in in biomedical language processing and text mining (bioNLP) in recent years, it is timely to ask if and how bioNLP techniques can be used to help address some of the rigor and integrity problems manifested in these artifacts. In this talk, I will motivate the use of bioNLP methods toward these goals by providing some use cases, and discuss a couple of tasks that I have recently pursued in this area: a) assessing clinical trial publications for reporting guideline adherence, and b) elucidating contradictory claims in biomedical publications. I will also highlight some of the challenges facing bioNLP research focusing on this area.

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Epigenomic insights of environmental disease

Zhibin Wang PhD

Dec 05, 2019|12:30 PM – 1:30 PM

130 University Health Services Building (Pizza & drinks served at 12:20. Please RSVP to

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Clinical Event Mining and Visualization for Chronic Rheumatic Diseases

Sujin Kim PhD

Nov 13, 2019|12:00 PM – 1:00 PM

UHS 130

Understanding the use of pattern mining algorithms and the development of a prototype system to visualize the relationships of frequent clinical events based on mined clinical sequences and associations.

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CANCELLED - Deciphering the regulatory code of metabolism in Arabidopsis - CANCELLED

Seung Yon (Sue) Rhee PhD

Nov 07, 2019|12:30 PM – 1:30 PM

Coordinated control of metabolic genes is crucial for plant development and adaptation to various environments. To discover general rules of metabolic regulation, we used omics data, machine learning, and experimental validation. To understand how metabolic genes are controlled by epigenetic marks, we mapped regulatory patterns of 16 epigenetic marks across metabolism in Arabidopsis and found a predominant regulatory pattern for specialized metabolic genes involved in controlling the precise timing of gene expression upon stimuli. To understand how transcription factors regulate metabolism, we constructed condition- and tissue-specific regulatory networks in Arabidopsis and identified patterns of transcriptional regulation at various levels. These studies elucidate metabolism coordination and contribute to developing toolkits for pathway engineering in plants.

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Reinforcement Learning for Brain Machine Interfaces

Jihye Bae PhD

Oct 17, 2019|12:30 PM – 1:30 PM

130 University Health Services Building

There have been promising advances in brain machine interfaces. However, many challenges still remain before this technology can become practical. In this talk, we will discuss some of the main issues along with possible approaches to overcome them. In particular, methods to translate neural signals to control external devices using reinforcement learning will be introduced.

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Transforming Ontologies into Nested Facet Systems

GQ Zhang PhD

Sep 19, 2019|12:30 PM – 1:30 PM

130 University Health Services Building

Irrespective of data size and complexity, query and exploration tools for accessing data resources remain a central linkage for human-data interaction. A fundamental barrier in making query interfaces easier to use,ultimately as easy as online shopping, is the lack of faceted, interactive capabilities. We propose to repurpose existing ontologies by transforming them into nested facet systems (NFS) to support human-data interaction. Two basic issues need to be addressed for this to happen: one is that the structure and quality of ontologies need to be examined and elevated for the purpose of NFS; the second is that mappings from data-source specific metadata to a corresponding NFS need to be developed to support this new generation of NFS-enabled web-interfaces. The purpose of this presentation is to motivate the concept of NFS, provide a preliminary order-theoretic formulation for NFS, and suggest topics for further investigation.

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Bacterial Outer Membranes and Interactions with Membrane Proteins

Wonpil Im PhD

Sep 05, 2019|12:30 PM – 1:30 PM

130 University Health Services Building (Pizza & drinks served at 12:20)

The outer membrane of gram-negative bacteria is a unique asymmetric membrane bilayer that is composed of phospholipids in the inner leaflet and lipopolysaccharides (LPS) in the outer leaflet. Its function as a selective barrier is crucial for the survival of bacteria in many distinct environments, and it also renders gram-negative bacteria more resistant to antibiotics than their gram-positive counterparts. LPS comprises three regions: lipid A, core oligosaccharide, and O-antigen polysaccharide. In this talk, I will present our ongoing efforts to understanding various bacterial outer membranes and their interactions with outer membrane proteins. In addition, I will also present other research projects in my lab, such as the CHARMM-GUI development, a local structure-centric bioinformatics for drug development, and structure.

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Mining electronic health records narratives for clinical research: The case of lifestyle modification

Eneida A. Mendonca MD, PhD, FAAP, FACMI

Jan 09, 2019|12:00 PM – 1:00 PM

University Health Services (UHS), room 130

This talk will address the importance of assessing lifestyle modification and behavior, and the challenges of using EHR data to identify lifestyle modifications and behavior in clinical narratives. Registration is required by January 8.

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The clinical and research informatics role in promoting a knowledge-drive medicine

Umberto Tachinardi MD, MS, FACMI

Jan 08, 2019| 8:00 AM – 9:00 AM

CT Wethington Building, room 127

Principles and practical examples demonstrating how biomedical informatics enables translational biomedical sciences, precision medicine, and a learning health system. Registration required by January 7.

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MS in Data Science at UK

Heather Bush, PhD, Miroslaw Truszczynski, PhD and GQ Zhang, PhD

Dec 12, 2018|12:00 PM – 1:00 PM

University Health Services (UHS) 130

A presentation of the curriculum and requirements of the proposed MS in Data Science degree program to be implemented at the University of Kentucky

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Commonwealth Computational Summit 2018

Oct 23, 2018| 8:30 AM – 6:00 PM

Bill Gatton Student Center

Featuring speakers from academia, industry, and government. Hosted by UK's Center for Computational Science. Must register to attend.

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Ninth Annual Therapeutics Outcomes Discovery & Delivery (TODD) Symposium: Precision Medicine, Genomics and Big Data

Sep 06, 2018| 8:00 AM – 5:30 PM

Lee T. Todd, Jr. Building, Room 124

Speakers include William Douglas Figg Sr, NIH; Atul Butte, University of California; Jill Kolesar, University of Kentucky; and Tim Tracy, Aprecia Pharmaceuticals.

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Standardizing CT images using generative adversarial networks

Jin Chen PhD

Jun 13, 2018|12:00 PM – 1:00 PM

University Health Service, room 130 (beside Employee Health)

Dr. Chen will discuss work to improve the analysis of CT images by developing models that learn to identify features from a set of training images and also generate synthetic images that display these features.

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Text mining in precision medicine: Opportunities and challenges

Hongfang Liu PhD

Jun 01, 2018|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Liu will review how text mining has been applied to precision medicine, and then discuss efforts at the Mayo Clinic.

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From Big Data to Bedside (BD2B): Precision oncology in an era of artificial intelligence

Xinghua Lu MD, PhD

May 16, 2018|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Lu will discuss how artificial intelligence technologies can provide insight to disease mechanism of individual tumors, cancer pathways, the state of signaling machinery in tumor cells, and the efficacy of anti-cancer drugs.

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Precision informatics at Cincinnati Children’s

Peter White PhD

Apr 30, 2018|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. White will discuss work at Cincinnati Children’s to educate stakeholders on informatics literacy and integrate biomedical and clinical data across the institution, as well as the social structures needed to support these efforts.

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Deep phenotyping on EHR narratives facilitates genetic diagnosis by clinical exomes

Chunhua Weng PhD

Mar 26, 2018|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Weng will describe a high-throughput EHR phenotype extraction and analysis framework that performs Human Phenotype Ontology (HPO) concept extraction and normalization from EHR narratives and prioritizes disease genes based on the HPO-coded phenotypic manifestations.

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CCTS Seminar Presentation:
SUDEP (Sudden Death in Epilepsy Patients)

Samden Lhatoo MD, DCRP

Jan 31, 2018|12:00 PM – 12:30 PM

Chandler Hospital, HG 611, Pavilion H 6th Floor

The CCTS and IBI present a lecture by Dr. Lhatoo, Professor of Neurology at Case Western Reserve University and Director of the Epilepsy Center at University Hospitals in Cleveland, OH.

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Biomedical ontologies in action

Olivier Bodenrider MD, PhD

Nov 07, 2017|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Olivier Bodenrider will discuss major biomedical ontolgies and their uses.

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1st annual Commonwealth Computational Summit

Oct 17, 2017| 8:30 AM – 5:30 PM

WT Young Library Auditorium, University of Kentucky

UK Center for Computational Science (CCS) is hosting this full day event for faculty, students, and industry professionals intrested in computational engineering, science, and data analytics.

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Similarity analytics in the age of precision medicine

Fei Wang PhD

May 11, 2017|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Fei Wang will discuss similarity analytics, a computational tool for identification of the similarity between pairwise data objects, and its applications in precision medicine.

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How computers see people

Nathan Jacobs PhD

May 10, 2017|12:00 PM – 12:50 PM

University Health Service Building, room 130

Nathan Jacobs, PhD, will discuss advances in machine learning that make it possible for computatal systems understand images of people. Hosted by CCTS. Registration required. Please email CCTS at to reserve your place by Tuesday, May 9, 2017.

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The questions and answers for biomedical data science

Jong Cheol Jeong PhD

May 09, 2017|12:00 PM – 12:50 PM

CT Wethington Building, room 014

Dr. Jong Cheol Jeong will discuss his work in translational bioinformatics and analysis of molecular data.

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Demonstrating the value of design research in biomedical informatics

Melissa Clarkson PhD, MDes, MA

Apr 27, 2017|12:00 PM – 1:00 PM

CT Wethington Building, room 127

Dr. Melissa Clarkson will present her research visualizing and auditing the Foundational Model of Antatomy, as well as her work combining visual and semantic representation.

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Feature selection and learning on high-dimensional and large-scale data

Qiang Cheng PhD

Apr 24, 2017|12:00 PM – 1:00 PM

CT Wethington Building, room 127

Dr. Cheng will discuss his work developing machine learning algorithms for big data and the minimax pattern learning framework.

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High-throughput biomedical image computing for digital health

Fuyong Xing

Apr 19, 2017|12:00 PM – 1:00 PM

Lee T Todd Building (BioPharm Complex), room 170

Fuyong Xing will discuss high-throughput biomedical image computing methods for digital health, focusing on object detection, segmentation, and image understanding in medical diagnosis.

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Humans, machines and the future of work

Apr 13, 2017| 4:00 PM – 5:00 PM

Chemistry-Physics Building, room 153

The Center for Computational Sciences, College of Engineering, Department of Computer Science and the Institute for Biomedical Informatics presents a distinguished lecture by Dr. Moshe Y. Vardi, Rice University.

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Trial prospector

Apr 12, 2017|12:00 PM – 1:00 PM

University Health Service Building, room 130

Shiqiang Tao, PhD, and Eric Durbin, DrPH, will present Trial prospector, a tool for management of clinical cancer trial recruitment workflow. Hosted by CCTS. Registration required. Please email CCTS at to reserve your place by Tuesday, April 11, 2017.

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Toward portable NLP solutions for healthcare — the journey of CLAMP

Hua Xu PhD

Mar 20, 2017|12:00 PM – 1:00 PM

CT Wethington Building, room 014

Dr. Hua Xu will describe CLAMP (Clinical language annotation, modeling, and processing), a clinical NLP system and interface for building custom NLP pipelines.

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Deep brain stimulation informatics

Cameron McIntyre PhD

Mar 14, 2017|12:00 PM – 1:00 PM

Lee T Todd Building, room 170

Dr. Cameron McIntyre will discuss how an informatics approach to deep brain stimulation could reduce treatment outcome variability.

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