June 24th - 25th 2025
BCEC Boston
Workshops
Workshops at the Festival provide a fantastic opportunity to bring your challenges to the table to get help, learn from experts and others who are going through the same things as you, and leave armed with new insights, tools, information and ideas to take back to your workplace.
Workshops are currently full. We have a waiting list in case any slots become available. You must be registered for the Festival to be considered for a workshop place.
Integrating Multi-Omics Data:
Unravelling Complex Biological Insights
Location: Room 050
Date & Time: 14:20 - 17:20 on Wednesday June 12th 2024
This workshop aims to give participants an introduction to the knowledge and practical skills needed to integrate and analyse multi-omics data effectively. The workshop will cover the theoretical foundations of multi-omics data integration and introduce accessible bioinformatics tools that could be used by wet lab scientists.
Learning Objectives
Develop an understanding of multi-omics data integration, recognising its significance, advantages, and challenges.
Become acquainted with popular bioinformatics tools for multi-omics integration and demonstrate basic proficiency in their utilisation.
Apply integrated multi-omics data analysis to real-life disease scenarios, identifying potential insights and avenues for therapy.
Explore emerging trends, ethical considerations, and collaborate with experts and peers to discuss insights and challenges in multi-omics research.
Workshop Agenda
Session 1 (45 minutes)
Bioinformatics Tools for Multi-omics Integration
Jeff Xia, Associate Professor, Canada Research Chair in Bioinformatics and Big Data Analytics, McGill University
Session 2 (30 minutes)
Introducing Hotgenes, R package for multi-omics data integration
Richard Virgen-Slane, Principal Computational Toxicologist, Pfizer
Session 3 (30 minutes)
Cellxgene VIP Unleashes Full Power of Interactive Visualization and Integrative Analysis of scRNA-seq, Spatial Transcriptomics, and Multiome Data
Baohong Zhang, Senior Director, Head of Translational Data Science, Biogen
Session 4 (30 minutes)
Multi-omics Integration Approach for Patient Heterogeneity and Risk Prediction
Tesfaye B. Mersha, Professor, Department of Pediatrics, Cincinnati Children's Hospital Medical Center
Future Directions, Challenges and Q&A with all instructors (15 minutes)
1. Emerging trends in multi-omics data integration (using deep learning techniques).
2. Ethical considerations and data sharing.
3. Open forum for participants to ask questions and discuss insights gained.
4. Recap of key takeaways and workshop conclusion.
Workshop Leaders:
Jeff Xia
Associate Professor, Canada Research Chair in Bioinformatics and Big Data Analytics, McGill University
Richard Virgen-Slane
Principal Computational Toxicologist, Pfizer
Baohong Zhang
Senior Director, Head of Translational Data Science, Biogen
Tesfaye B. Mersha
Professor, Department of Pediatrics, Cincinnati Children's Hospital Medical Center
Workshop Agenda
Session 1 (15 minutes)
Overcoming Data Challenges to Personalize Gut Microbiome Interventions: The Importance of Reproducibility in Microbiome Studies
Andrea Peril-Azcarate, Professor of Medicine, Director of UNC Microbiome Core, Adjunct Professor of Nutrition, UNC School of Medicine
Session 2 (15 minutes)
Novel Interpretable Deep-Learning Methods for Analyzing the Microbiome to Improve Human Health
Georg Gerber, Chief, Division of Computational Pathology, Co-Director, Massachusetts - Host-Microbiome Center
Session 3 (15 minutes)
Transforming Microbiome-Based Therapeutics
Jason Norman, Senior Director, Systems Biology, Vedanta Biosciences
Session 4 (15 minutes)
Using High-Throughput Genomic Technologies to Study Host-Microbe Interactions
Ran Blekhman, Associate Professor, University of Chicago
Propelling Microbiome Metagenomics Research from the Bedside to the Clinic:
Deep-Dive into Data, Development & Translation Challenges
Location: Room 050
Date & Time: 11:40 - 13:10 on Wednesday June 12th 2024
Although microbiomes are invisible to the naked eye, their influence on human health, such as in infectious diseases and neurological disorders, is significant. Despite their crucial role, obstacles persist in effectively translating microbiome research into the clinic. This workshop aims to shed light on the current translational progress, including data approaches, in leveraging the gut microbiota to address human diseases. The workshop will spark discussions about the opportunities and hurdles in the successful use of microbiome metagenomic data, which improve the understanding of microbial cell biology and the development of drugs and therapeutics. If you are wondering how to improve the translation of your microbiome research through data integration, analysis and omics, look no further as you engage in discussions guaranteed to revolutionise your pipelines.
Learning Objectives
Gain insights into the progression of the preclinical and clinical landscapes within drug development
Discuss how the discovery of the microbiome and its role in human health has revolutionized our understanding of disease and led to the development of new therapeutic approaches
Unravel data challenges and opportunities that hinder robust data usage and integration
Delve into the data approaches used to transform healthcare, including personalized medicine approaches tailored to everyone's microbiome through omics
Workshop Leaders
Andrea Peril-Azcarate
Professor of Medicine, Director of UNC Microbiome Core, Adjunct Professor of Nutrition, UNC School of Medicine
Georg Gerber
Chief, Division of Computational Pathology, Co-Director, Massachusetts - Host-Microbiome Center
Jason Norman
Senior Director, Systems Biology, Vedanta Biosciences
Ran Blekhman
Associate Professor, University of Chicago
Deriving Novel Insights from Single-Cell Data
Location: Genome Dome
Date & Time: 14:00 - 15:30 on Thursday June 13th 2024
It has long been understood that single-cell analysis is crucial to our understanding of cellular heterogeneity, signalling pathways and disease mechanisms. While the advent of spatial has attracted significant attention, we must still make the best use of the huge single-cell data available at our fingertips.
This workshop is aimed to help people understand the single-cell data analysis workflow, and how we can leverage existing datasets to our advantage to uncover novel insights hidden in the data.
Learning Objectives
Discover how to leverage existing single-cell data to help propel your current research forward
Learn methods for analysing your single-cell data, and hear examples of how these have gained novel insights
Hear about how to translate pre-clinical observations into human disease insights
Workshop Agenda
Session 1 (30 minutes)
Translating Pre-Clinical Observations to Human Disease
1. Discuss the role single-cell data plays in bridging the gap between pre-clinical observations of human disease,
2. Two lightning talks and explore methodologies.
Making the Most of your Single-Cell Data to Fuel Discovery
Marc Wadsworth, Principal Scientist, Pfizer
Session 2 (30 minutes)
Leveraging Atlasing and Multi-Omics to Facilitate New Discoveries.
1. Discuss how multi-omics and atlasing projects can help facilitate new discoveries.
2. Demonstrate how to navigate legacy data and give an overview of popular integration methods.
Revealing Novel Targetable Biology with Multi-Omic Approaches
Mathew Chamberlain, Principal Scientist, Janssen
Session 3 (30 minutes)
Methods to Infer Insights
An overview of computational methods that are useful for underpinning new insights, introduce the methods and show you where you can access more information.
Single-Cell & Bioinformatic Tools to Accelerate Drug Target Discovery
Aridaman Pandit, Senior Principal Scientist, AbbVie
Workshop Leaders:
Marc Wadsworth
Principal Scientist, Pfizer
Mathew Chamberlain
Principal Scientist, Janssen
Aridaman Pandit
Senior Principal Scientist, AbbVie
Spatial Data Analysis
Location: Room 050
Date & Time: 11:30 - 15:30 on Thursday June 13th 2024
This workshop aims to provide participants with an introduction to the methods and tools available to make the best of Spatial omics data. It will provide an overview of various methods and help researchers to choose a method to suit their needs.
Learning Objectives
Get introduced to the data analysis methods to integrate spatial data with sequencing and multi-omics data
Discover tools that have been developed that can help propel your research forward
Hear case studies where novel insights have been gained from utilising these tools, and what data analysis challenges remain unanswered for the community
Workshop Agenda
Session 1 (1.5 hours)
Integrating Sequencing and Imaging Data
An introduction to spatial data analysis
Miko Liu, PhD Candidate, Duke University
Spatial-Omics To Interrogate Host-Disease Interactions
Sizun Jiang, Assistant Professor of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School
Multiplexed 3D Analysis of Cell Plasticity and Immune Niches in Melanoma
Ajit Nirmal, Principal Investigator, Brigham and Women's Hospital
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Session 2 (1.5 hours)
Analysis Tools
An Introduction to spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data
Leonardo Collado Torres, Investigator, Lieber Institute for Brain Development
An Introduction to Monkeybread
Matthew Bernstein, Principal Scientist, Immunitas Therapeutics
Discussion and Q & A
Workshop Leaders
Miko Liu
PhD Candidate, Duke University
Sizun Jiang
Assistant Professor of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School
Ajit Nirmal
Principal Investigator, Brigham and Women's Hospital
Leonardo Collado Torres
Investigator, Lieber Institute for Brain Development
Matthew Bernstein
Principal Scientist, Immunitas Therapeutics
The NIH Common Fund Data Ecosystem: Catalyzing Discovery by Integrating Data Across Biomedical Research Domains
Location: Genome Dome
Date & Time: 11:30 - 13:00 on Thursday June 13th 2024
In this workshop we will introduce the wide range of biomedical data and knowledge available via the NIH Common Fund Data Ecosystem (CFDE). The CFDE consists of 14 programs conducting innovative research in areas ranging from molecular biology to rare disease genetics to mammalian physiology, including well-known and heavily used resources such as GTEx and HuBMAP. These programs are brought together in the CFDE with the aim of enabling cross-domain hypothesis generation to benefit human health research.Two resources empower access to and exploration of CFDE results. The CFDE Data Resource center provides direct access to data and cloud-based tools to interrogate datasets, while the CFDE Knowledge Center curates, integrates, and visualizes knowledge across CFDE programs.Attendees will gain an overview of the CFDE and learn how to access and query its data and knowledge..
Workshop agenda
Introduction and welcome
Noel Burtt, Director of Operations and Development for Knowledge Portals and Diabetes Research, The Broad Institute of MIT and Harvard
Session 1: The 4D Nucleome
Peter Park, Professor of Biomedical Informatics, Harvard Medical School
1. I will describe the Hi-C and other chromosomal interaction data collected in the 4D Nucleome project to investigate the role of nuclear organization in gene regulation.
2. I will give an overview of our cloud-based platform and the challenges of building and maintaining a data portal.
Talk 2: Playbook Workflow Builder: Interactive Construction of Bioinformatics Workflows from Digital Object Building Blocks
Daniel Clarke, Biomedical Software Developer, Ma’ayan lab, Icahn School of Medicine at Mount Sinai
1. User-friendly web-based interface to construct bioinformatics workflows
2. Publication ready reports created directly from uploaded data
3. A growing connected network of over 500 workflow building blocks
Session 3: Crosscut Metadata Model Search Engine for the CFDE Data Portal
Sumana Srinivasan, Postdoctoral Research Scholar, Subramaniam lab, University of California San Diego
1. Metadata model to harmonize datasets from over ten 10 Common Fund prgrams
2. Graph-based database for storing metadata about diverse biomedical data · Filters and shopping carts to aid users find and use selected digital assets
Session 4: Incorporating Generative AI Models in Omics Bioinformatics Workflows
Avi Ma’ayan, Mount Sinai Endowed Professor in Bioinformatics, Professor, Department of Pharmacological Sciences, Director, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai
1. Hypotheses generation by LLM crossing datasets and publications
2. Mining gene sets from PMC and GEO
3. Prompting a chatbot to produce data analysis results via tools' API
Workshop Leaders
Peter Park
Professor of Biomedical Informatics, Harvard Medical School
Avi Ma’ayan
Mount Sinai Endowed Professor in Bioinformatics, Professor, Department of Pharmacological Sciences, Director, Mount Sinai Center for Bioinformatics, Icahn School of Medicine at Mount Sinai
Noël Burtt
Director of Operations and Development for Knowledge Portals and Diabetes Research, The Broad Institute of MIT and Harvard
Daniel Clarke
Biomedical Software Developer, Icahn School of Medicine at Mount Sinai
Sumana Srinivasan
Postdoctoral Research Scholar, Subramaniam lab, University of California San Diego
