Microorganisms exhibit immense diversity, occupying countless ecological niches throughout evolution. These microorganisms form complex microbial communities that significantly influence their environment, such as in the human gut, and host health. Identifying individual species within these communities is crucial for detecting disturbances and health-related issues. In this webinar, we will explore the application of nanoplate digital PCR (dPCR) for the accurate detection and quantification of key microbial target species. We will also discuss best practices for multiplexing multiple microbial assays within a single dPCR reaction, highlighting the advantages of this technology in advancing microbiome research.

Understanding the tumor microenvironment (TME) presents a major challenge for biopharma researchers and translational scientists. The complexity of cellular interactions, variability across patient samples, and overwhelming volume of public omics data can make it difficult to pinpoint key molecular drivers and predict functional consequences. Building a clear, actionable view of the TME often feels like assembling a puzzle without the picture on the box.

In this webinar, discover how QIAGEN Ingenuity Pathway Analysis (IPA) can help overcome these challenges by combining expertly curated biological knowledge with powerful predictive modeling tools. Learn how to easily construct molecular networks, interpret gene expression data from resources like TCGA and GEO, and model upstream regulators to predict immune and tumor behavior. Using examples such as IL1B’s role in non-small cell lung cancer (NSCLC), we’ll show you how IPA can accelerate your discoveries and guide therapeutic insights.

What you’ll learn:

• How to identify disease-associated molecules and visualize their biological interactions
• How to mine and interpret public gene expression data for deeper insights into cancer biology
• How to model upstream regulators and predict functional outcomes within the TME

Understanding the tumor microenvironment (TME) presents a major challenge for biopharma researchers and translational scientists. The complexity of cellular interactions, variability across patient samples, and overwhelming volume of public omics data can make it difficult to pinpoint key molecular drivers and predict functional consequences. Building a clear, actionable view of the TME often feels like assembling a puzzle without the picture on the box.

In this webinar, discover how QIAGEN Ingenuity Pathway Analysis (IPA) can help overcome these challenges by combining expertly curated biological knowledge with powerful predictive modeling tools. Learn how to easily construct molecular networks, interpret gene expression data from resources like TCGA and GEO, and model upstream regulators to predict immune and tumor behavior. Using examples such as IL1B’s role in non-small cell lung cancer (NSCLC), we’ll show you how IPA can accelerate your discoveries and guide therapeutic insights.

What you’ll learn:

• How to identify disease-associated molecules and visualize their biological interactions
• How to mine and interpret public gene expression data for deeper insights into cancer biology
• How to model upstream regulators and predict functional outcomes within the TME

Understanding the tumor microenvironment (TME) presents a major challenge for biopharma researchers and translational scientists. The complexity of cellular interactions, variability across patient samples, and overwhelming volume of public omics data can make it difficult to pinpoint key molecular drivers and predict functional consequences. Building a clear, actionable view of the TME often feels like assembling a puzzle without the picture on the box.

In this webinar, discover how QIAGEN Ingenuity Pathway Analysis (IPA) can help overcome these challenges by combining expertly curated biological knowledge with powerful predictive modeling tools. Learn how to easily construct molecular networks, interpret gene expression data from resources like TCGA and GEO, and model upstream regulators to predict immune and tumor behavior. Using examples such as IL1B’s role in non-small cell lung cancer (NSCLC), we’ll show you how IPA can accelerate your discoveries and guide therapeutic insights.

What you’ll learn:

• How to identify disease-associated molecules and visualize their biological interactions
• How to mine and interpret public gene expression data for deeper insights into cancer biology
• How to model upstream regulators and predict functional outcomes within the TME

Understanding the tumor microenvironment (TME) presents a major challenge for biopharma researchers and translational scientists. The complexity of cellular interactions, variability across patient samples, and overwhelming volume of public omics data can make it difficult to pinpoint key molecular drivers and predict functional consequences. Building a clear, actionable view of the TME often feels like assembling a puzzle without the picture on the box.

In this webinar, discover how QIAGEN Ingenuity Pathway Analysis (IPA) can help overcome these challenges by combining expertly curated biological knowledge with powerful predictive modeling tools. Learn how to easily construct molecular networks, interpret gene expression data from resources like TCGA and GEO, and model upstream regulators to predict immune and tumor behavior. Using examples such as IL1B’s role in non-small cell lung cancer (NSCLC), we’ll show you how IPA can accelerate your discoveries and guide therapeutic insights.

What you’ll learn:

• How to identify disease-associated molecules and visualize their biological interactions
• How to mine and interpret public gene expression data for deeper insights into cancer biology
• How to model upstream regulators and predict functional outcomes within the TME

The host-associated microbiome interacts extensively with the host’s metabolism and immune system, playing a key role in health and function. Symbiosis and dysbiosis affects cancer, autoimmune disease, allergies, asthma and various metabolic disorders. Studying microbiome composition through metagenomic next-generation sequencing (NGS) is the key to discovering the influences of host-microbiome interactions. Unfortunately, microbial DNA may be a vanishingly small amount of the total DNA and is often eclipsed by host DNA in libraries. This leaves few reads for microbial genome analysis, leading toextremely high sequencing costs per useful read. And when resources are tight, every read counts. Thus, we have developed a protocol that depletes host DNA in tissue, swab and bodily fluids to a negligible amount. In this webinar, we will present this protocol, data and a new kit that depletes host-DNA to better target microbes and the microbiome.

In order to develop optimal workflows for NGS analysis of microbes and microbiomes, having a dedicated toolbox for the tasks at hand helps with achieving high sensitivity and finding the proverbial needle in the haystack. Dedicated tools include bioinformatic tools for depletion of host-derived reads, tools and databases for metagenomic analysis. Here, we will introduce the tools, show how to string them together in workflows and interactively explore results using the QIAGEN CLC Genomics Workbench.

The host-associated microbiome interacts extensively with the host’s metabolism and immune system, playing a key role in health and function. Symbiosis and dysbiosis affects cancer, autoimmune disease, allergies, asthma and various metabolic disorders. Studying microbiome composition through metagenomic next-generation sequencing (NGS) is the key to discovering the influences of host-microbiome interactions. Unfortunately, microbial DNA may be a vanishingly small amount of the total DNA and is often eclipsed by host DNA in libraries. This leaves few reads for microbial genome analysis, leading toextremely high sequencing costs per useful read. And when resources are tight, every read counts. Thus, we have developed a protocol that depletes host DNA in tissue, swab and bodily fluids to a negligible amount. In this webinar, we will present this protocol, data and a new kit that depletes host-DNA to better target microbes and the microbiome.

In order to develop optimal workflows for NGS analysis of microbes and microbiomes, having a dedicated toolbox for the tasks at hand helps with achieving high sensitivity and finding the proverbial needle in the haystack. Dedicated tools include bioinformatic tools for depletion of host-derived reads, tools and databases for metagenomic analysis. Here, we will introduce the tools, show how to string them together in workflows and interactively explore results using the QIAGEN CLC Genomics Workbench.