Artificial Intelligence and Machine Learning – Webinars and Online Events

Using the example of tumor-associated macrophages (TAMs), this webinar takes a closer look at immune cells in the tumor microenvironment (TME), helping us to gain a better understanding of how specific subtypes and their reprogramming may influence therapy efficiency.

In this webinar, Dr. Luciane Kagohara from Johns Hopkins Medicine will discuss a novel artificial intelligence method integrating imaging, spatial transcriptomics and single-cell RNA-seq data that has been used to characterize the cell state transitions in pancreatic cancer progression.

Multiple solutions have been devised to increase multiplexing in qPCR, including single-well techniques, using target-specific fluorescent oligonucleotide probes, and spatial multiplexing, where
segregation of the sample enables parallel amplification of multiple targets.

There is a need for innovations that will push forward the multiplexing field in qPCR, enabling for the next generation of diagnostic tools which could accommodate high throughput in an affordable manner. To this end, the use of machine learning algorithms has recently emerged to leverage information contained in amplification and melting curves– two of the most standard biosignals emitted during qPCR – for accurate classification of multiple nucleic acid targets in a single reaction.

Thermo Fisher Scientific are not affiliated with the webinar speaker. Any application of machine learning technologies with the Diomni™ software package, related assay definition files (ADFs) and related qPCR instruments are for research use only.

In this webinar, our expert speaker Dr. Phillip Kim from the University of Toronto will be discussing the ML methods he currently implements in his lab that enables de novo antibody design. He will also cover ML-based sequence design and scoring methods, as well as diffusion models.

Introducing midia-PASEF®, a groundbreaking DIA scan mode utilizing overlapping quadrupole windows for comprehensive ion analysis.

This exclusive AMA event grants you unprecedented access to the pioneering expert Prof. Michael Snyder a distinguished professor at Stanford University known for his ground-breaking work in digitalizing scientific research in the genomics and personalized medicine field.

In today’s world, laboratories are constantly pushed to be faster, more effective, more accurate, with less waste and cost. At the same time emerging technologies provide labs with an opportunity to change the way they work today making them more efficient and effective. Leveraging these technologies will determine the success of your lab to evolve into the lab of tomorrow.

Artificial Intelligence (AI) and Machine Learning (ML) are rapidly entering the day-to-day operations of many organizations, and data efforts are in full force.

Organizations, across all scientific industries, are assessing their digital transformation journey to try and map out the key strategies to achieving a fully digitally enabled laboratory. The key to creating and implementing a digital strategy is determining where efficiencies can be made and where technologies can provide a competitive edge.