Data Talks

KNIME Data Talks - Lab Data

April 22, 2021 - Online
KNIME Data Talks - Laboratory Data

Many life science companies have large digitalization initiatives, which include a focus on laboratory data. However, challenges such as inconsistent infrastructures, poor or lacking integration interfaces, and varied personal skill sets make it difficult to both implement these initiatives and realize the promised benefits (e.g. improved experimental reproducibility, reduction in errors, increased productivity, etc.).

In this online event we bring together a group of experts to discuss and demonstrate how KNIME can help to tackle these challenges.

We’ll look at analyzing and integrating diverse data (e.g., images, assay, or spectra), enriching such data through contextualization, and talk about how KNIME can help ease user adoption and facilitate the automation of laboratory processes by integrating laboratory standards.


NOTE: This online event is being held on Thursday April 22, 2021 at 3 PM - 5 PM UTC +2 (Berlin) which is 8 AM - 10 AM UTC -5 (Chicago).


Agenda Overview

Welcome
Jeanette Prinz – KNIME

The Value of End-to-End Lab Automation
Rob Harkness – Biosero

How SiLA Supports Open Interoperability in the Laboratory
Patrick Courtney – Standardization in Lab Automation (SiLA) Consortium

Measurement of Cell Density with KNIME and SiLA for Cell-culture
Michael Koeppl – Hit Discovery Constance GmbH

Using KNIME to FAIRify Data
Alice Krebs – KNIME

Chemometrics with KNIME – Analysis of NIR Data
Miriam Mathea – BASF SE

Challenges in Lab Digitization Efforts (Panel Discussion)
Speakers TBA

FAQ
How do I join the KNIME Data Talks?

You’ll receive a link with your registration confirmation. We're using Bizzabo as a streaming platform. Make sure you have a stable internet connection!

Will I be able to ask questions?

Sure! Use the Q&A tool in Bizzabo to ask your question and we'll answer them live. 

Where do I find the latest version of KNIME Analytics Platform?

Download the latest free, open source version of KNIME here: knime.com/download

What other resources will help me to get started in KNIME?
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