Excited to share our vision for bioinformatics education available for students and researchers that want to apply advanced multi-omics integration and machine learning to large biomedical datasets. Practice and learn from real-life projects.

1. Project-based education in Computational
Analytics for Biomedical Data and Bioinformatics
OMICSLOGIC: A HYBRID ONLINE/OFFLINE LEARNING MODEL

2. EDUCATIONAL OBJECTIVES
In the Bioinformatics “OmicsLogic” program,
participants will experience hands-on, project-
based learning that combines scientific inquiry,
critical thinking and problem solving while
participating in research-oriented analysis of large-
scale biomedical data.
To achieve these goals, we designed a
comprehensive bioinformatics environment that
combines interactive online learning tools with a
research-grade analysis platform and curated
datasets from impactful scientific publications.
Our online learning environment provides in-
depth evaluation with real-time feedback and
allows us to conduct meaningful hands-on
workshops online and on-site. The learning
experience engages both students and faculty,
facilitating real inquiry and problem solving.
These objectives follow the New Generation
Science Standards that identify learning as a
combination of knowledge and practice, focusing
on “integration of rigorous content with the
practices that scientists use in their work” and
highlight the importance of the development of
integrated environments that enable students to
learn science by participating in research.
The curated projects are designed to building a
strong background in translational research that
utilizes multi-omics datasets and developing an
understanding of the significance of such
methodologies in biomedical applications.
The program provides opportunities to
develop critical thinking as an approach to
digesting scientific literature by hands-on
experience of methods and practices that
scientists use in their work, including
application of statistics to detect patterns in
big data and utilize biomedical knowledge to
interpret such findings.
OmicsLogic is about increasing career
readiness in biomedical/biotech industries by
giving increased attention to the practices
that scientists routinely use. Learning about
the application of mathematical techniques
and familiarity with biological concepts to
develop a logical approach for utilization of
big biomedical data resources. The program
also has a clear objective - to help more
young scientists apply advanced methods in
multi-omics data analysis and integration
methods relevant to critical fields of
innovation: oncology, neuroscience,
agrotech, virology and other important
disciplines.
Our online learning environment
provides in-depth evaluation with
real-time feedback and allows us
to conduct meaningful hands-on
workshops online and on-site.
We designed a comprehensive
bioinformatics environment that
combines interactive online
learning tools with a research-
grade analysis platform and
curated datasets from impactful
scientific publications.
Experience hands-on, project-
based learning that combines
scientific inquiry, critical thinking
and problem solving while
participating in research-oriented
analysis of large-scale biomedical
data.
PROJECT-BASED LEARNING
RESEARCH-GRADE TOOLS
JOINT PROBLEM-SOLVING
2017

3. The T-BioInfo platform is a single environment to process various biological data. We designed it to simplify access by eliminating the need to download, install
and troubleshoot a whole range of programs and to avoid switching from one to another (which increases analysis time and introduces errors in your raw data). The
platform has an interface that seeks to reduce the number of options and offer best suggestions for next step of analysis along the way. The interface adapts to user
selection and provides informational pop-ups during the process of pipeline creation. The platform runs on High Performance Computing (HPC) infrastructure
utilizing advanced approaches developed at the Tauber BioInformatics Research Center at the University of Haifa, Israel.
T-BIOINFO PLATFORM: RESEARCH GRADE COMPUTATIONAL ANALYSIS TOOL FOR MULTI-OMICS

4. OMICSLOGIC: COMBINING THEORETICAL LEARNING IN BIOINFORMATICS WITH ANALYSIS LOGIC
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1.A course on a selected specialization track (i.e. Oncology) is selected. This specialization track determines
the “topic” of each subsequent course, such as “Transcriptomics 1” that covers the theoretical background
and terminology about the basics of genetics, cellular biology and associated data generation techniques.
2.The selected course is customized by selection of relevant datasets, taken from publications in the field of
the topic of study. Additional terminology and highlights from the topic are applied to enrich the content of
the course.
3.The relevant projects are broken down into data types and data “chunks”, to demonstrate data preparation,
processing, exploration and analysis in practical exercises that are ready to be deployed on the T-BioInfo
platform.

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APPLICATION AND EVALUATION OF LEARNING
3. Loading of data chunks (project and/or publication source) onto the platform
determines the focus of the analysis
4. The T-BioInfo platform offers several suggestions during the pipeline creation process.
These suggestion engine minimizes errors from inexperienced users and resulting
pipelines can be compared and contrasted to evaluate their function and logic.
5. As the pipeline is built, each “button” displays an informational pop-up that deepens
the educational experience
6. A pipeline output has to be analyzed visualizing the data, and applying advanced
machine learning tools that have a common function to any project, but also have
limitations or use-cases when they might be used more efficiently.
7. Finally, the activities are evaluated by factors recorded on the platform and quizzes and
the analyzed data is reviewed within the context of a studied topic (i.e. Oncology) to
produce biologically interpretable outputs.

6. Kick-off
Workshop
3 hours
Hands-on
practical review
6 hours (2 days)
Hands-on
Advanced
3 hours
Project
review
3 hours
• Big data challenges in
biology and biomedicine
• Hypothesis-free analysis
• Biomedical Applications of
Bioinformatics
• Next Generation Sequencing
• Raw NGS processing
(alignment, gene expression
quantification)
• Principle Component
Analysis (PCA)
• t-test statistics
• Differential Gene Expression
• Isoforms vs. Genes
• Limitations of standard
methods
• Machine Learning
• Unsupervised methods: PCA
and clustering techniques
• Building a supervised model
for classification
• LDA, SVM, Decision Trees
independent project
Beginner
HANDS-ON HYBRID PROGRAM OVERVIEW
*after 9 hours of
dedicated study
*after 50 hours of
dedicated study
1-2 h 3-4 h 3-4 h 5-6 h
**

7. ONLINE COURSES: EDU.T-BIO.INFO
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1. Clear outline of courses marked as
completed
2. Glossary of terms accessible on-
demand
3. diagrams simplifying complex algorithmic
explanations
4. chat box live and active throughout the
lessons

8. INDEPENDENT PROJECTS (ONCOLOGY SPECIALIZATION EXAMPLE)
Projects are prepared from high impact publications relevant to the specialization. Public domain datasets are curated to prepare focused assignments illustrating how the data
is processed and used to achieve similar results to the publication. Other approaches that can perform a similar function are discussed, providing a review of the methods
section of the paper. Finally, full dataset is organized into a project format that can be analyzed for discovery.

9. WORKSHOPS: REMOTE AND ON-SITE LEARNING WITH JOINT CERTIFICATION
REMOTE VIA VIDEO STREAM AT UNIVERSITY OF NEBRASKA MEDICAL CENTER) ON-SITE WORKSHOP FOR GRADUATE STUDENTS AT GEORGETOWN UNIVERSITY
Remote workshops have a
demonstrated value of easy access for
students in remote areas and limited
funding for travel. This is an affordable
solution that is still practical using video
streaming and chat-like communication
with an organizer present at the event
location. This model also works for
online students joining in with an on-
site event. We tested this model with
the University of Nebraska Medical
Center with over 50 students attending
a 3-hour workshop.
On-site workshops are more expensive, but have
greater impact, especially for students wanting to
learn how to apply analysis tools to their own
datasets. These events can attract a better
prepared audience that already has taken a
number of online courses and developed
questions and ideas that they need feedback on
or help with.
Both types of workshops can be jointly certified
by the hosting institution and our team - a
collaboration between Pine Biotech and
researchers at the Tauber Bioinformatics
Research Center.

10. PRE- AND POST- ASSESSMENT SURVEYS:
Pre- and Post- assessment is performed to evaluate skills, theoretical and applied understanding of the
topics covered in courses and projects. In the example on the left, a pre-assessment survey demonstrates
how an abstract from a publication along with figures described in the methods section can be used to
evaluate how well a participant understands a studied topic.
Survey examples on top show how key terms and logic around practical use of methods evaluated during
the course are evaluated.
These surveys are spread out through the course to provide insight into student progress and effect of
practical activities on development of analysis logic.

11. ONGOING PILOTS AND PARTICIPATING INSTITUTIONS
Georgetown