tv.qiagenbioinformatics.com

Comorbidity data can reveal unexpected and insightful connections between diseases. Understanding shared risks and underlying mechanisms are critical for informing patient care, yet these analyses often present significant challenges for researchers.

Using a case study on the correlation between asthma and inflammatory bowel disease (IBD) in women, this webinar will demonstrate how comorbidity data can be integrated with harmonized omics datasets and knowledge graph–based analytical approaches.

Discover how you can combine large-scale, preprocessed omics resources with network-driven analytics to uncover shared molecular mechanisms across diseases. Leveraging extensive collections of preprocessed data, the approach identifies gender-specific differentially expressed genes within each disease condition. Findings are then contextualized within a molecular interaction network to clarify associated biological functions and support hypothesis generation.

This webinar is based on a 2022 NHS population study on multimorbidity and comorbidity1, which demonstrates how large-scale datasets can be used to propose mechanistic hypotheses that help explain observed patterns in patient health.

Reference:

[1] Kuan, Valerie, et al. “Identifying and visualizing multimorbidity and comorbidity patterns in patients in the English National Health Service: a population-based study.” The Lancet Digital Health 5.1 (2023): e16-e27.

Biomedical KB-HD analysis in Neo4j enables researchers to explore complex relationships between drugs, targets and diseases using a comprehensive biomedical knowledge graph. Explore how to use this expert-curated data to identify promising disease biomarkers and examine their targets for various applications, using GLP-1, diabetes and Alzheimer’s disease as an example.

You will learn:

- To query BKB-HD in Neo4j to identify relevant drug candidates

- To investigate connected biology by linking drugs, targets and disease associations

- To export and visualize findings to support interpretation and hypothesis generation

Learn more about Biomedical KB-HD.

Influenza is a highly contagious disease that affects humans and multiple animal hosts. Since influenza viruses are prone to major genetic changes, continuous research is critical for global public health, enabling scientists to anticipate and mitigate the impact of this rapidly evolving pathogen.

Our webinar will show how you can analyze and interpret influenza virus sequencing data using QIAGEN CLC Genomics Workbench. Using the Microbial Genomics Module, we will explore influenza strain typing on targeted sequencing data, starting from raw FASTQ files or publicly available datasets.

You will learn to:

• - Use a pre-built workflow for influenza strain typing or set up your own

• - Customize influenza reference datasets to improve typing accuracy

• - Analyze and interpret strain typing results

Welcome to one of our exclusive, hands-on virtual workshops to explore Franklin + HGMD Professional — a powerful variant interpretation and reporting solution combining AI-driven workflows with expertly curated evidence.

During this session, you’ll analyze a real-world case involving a 3-month-old patient with complex neuromuscular phenotypes. Using Franklin + HGMD, you’ll prioritize variants, explore curated evidence (including disease-causing mutations from HGMD), and see how seamlessly the platform integrates clinical data, expert recommendations, and insights from 100+ databases.

You’ll also discover how Franklin + HGMD:

• - Uses advanced AI to prioritize and classify variants efficiently

• - Automates ACMG classification with integrated HGMD and ClinGen guidance

• - Enables customizable, AI-assisted reporting for actionable clinical insights

Welcome to one of our exclusive, hands-on virtual workshops to explore Franklin + HGMD Professional — a powerful variant interpretation and reporting solution combining AI-driven workflows with expertly curated evidence.

During this session, you’ll analyze a real-world case involving a 3-month-old patient with complex neuromuscular phenotypes. Using Franklin + HGMD, you’ll prioritize variants, explore curated evidence (including disease-causing mutations from HGMD), and see how seamlessly the platform integrates clinical data, expert recommendations, and insights from 100+ databases.

You’ll also discover how Franklin + HGMD:

• - Uses advanced AI to prioritize and classify variants efficiently

• - Automates ACMG classification with integrated HGMD and ClinGen guidance

• - Enables customizable, AI-assisted reporting for actionable clinical insights

QIAGEN OmicSoft Explorer is your portal to thousands of deeply curated and integrated ‘omics datasets. In this hands-on workshop, we will explore projects with cell-level data and use it to investigate relevant studies, diseases or genes of interest using curated metadata terms. See how you can use OmicSoft Explorer by itself or with Ingenuity Pathway Analysis (IPA) to accelerate biological insights.

You will learn:

• To search for a project based on user-defined metadata and explore dimension reduction plots to visualize clustering

• To identify cell types expressing a gene of interest and study volcano plots to identify biomarkers associated with cell types of interest

• To access and use IPA Interpret for statistical comparisons

ATAC-seq is a powerful technique for assessing chromatin accessibility and identifying regulatory regions across the genome. From bulk ATAC-seq for population-level findings to single-cell ATAC-seq (scATAC-seq) to resolve chromatin accessibility at the individual cell level, these approaches lend deeper insights into gene regulation and cell state.

QIAGEN CLC Genomics Workbench Premium provides researchers with a single, flexible platform for the analysis of both bulk ATAC-seq and scATAC-seq data. In this webinar, we’ll showcase the Workbench’s ATAC-seq analysis workflows, such as:

• Data processing and QC, including read quality control, deduplication and comprehensive reporting

• Core analysis steps, including peak calling, nearby gene identification and transcription factor motif analysis

• Biological interpretation and visualization, including clustering, automated cell type prediction for single-cell data and visualizations (UMAP plots, dot plots, heat maps and violin plots)

This 90-minute training session will show you how QIAGEN Ingenuity Pathway Analysis (IPA) helps visualize molecular intricacies and variations at multiple levels, such as transcriptome, proteome and metabolome. Through a series of brief technical vignettes, we will demonstrate how to:

- Generate associations among molecular signatures obtained via integrating multi-omics data

- Extract mechanisms from multi-omics data for precision medicine

- Disease stratification based on multi-omics profiles

- Map disease networks among targets and indications

One click from your target gene to disease drivers, drug candidates and causal evidence. The Neo4j & QIAGEN solution transforms causal biomedical knowledge from QIAGEN Discovery KB+ into an interactive discovery surface. Learn how to query biomarkers, navigate causal networks and find drug repositioning candidates,  provenance and natural language summaries included.

NVIDIA and QIAGEN are collaborating to bring trustworthy, contextual AI to drug discovery. By integrating NVIDIA's accelerated computing and the BioNeMo platform with QIAGEN Digital Insights' manually curated biomedical knowledge graphs, cited in over 70,000 peer-reviewed publications; the collaboration aims to transform how disease mechanisms, therapeutic targets, and biomarkers are identified. Using a graph-based AI approach built on G-Retriever, the solution delivers 5–10x better performance than standard RAG pipelines, giving researchers answers they can trust, defend, and act on. In this conversation from Bio-IT World 2026, NVIDIA's Ben Busby and QIAGEN's Venkatesh Moktali discuss what each side brings, why knowledge graphs are a must-have for pharma AI, and what's coming next — including initial pilots with select pharma and biotech partners ahead of broader availability.