Bioanalytics
Martyna Pawletta, MA
Data Scientist
KNIME
Berlin, Berlin, Germany
Corey Weisinger
Data Scientist
KNIME
Austin, Texas
Description: Nowadays there are many tools available that allow you to analyze data. Many of them require coding experience or are limited to certain scientific areas. Often they require you to spend a significant amount of time learning how to use them before you really can start with real data analysis.
In this presentation, we will introduce an open source platform that allows you to put more focus on your research and on answering scientific questions, instead of on coding or on learning how to code. You will learn how to visually build workflows and analyze your data. Especially in Life Sciences, visual low-code tools become very useful for experimental scientists, chemists, biologists, clinicians and other data experts to create reproducible and reusable data-driven solutions.
We will also show different use cases coming from Life Sciences research and industry. To this end, we selected areas such as cheminformatics and drug discovery, text mining to analyze scientific literature, as well as clinical data cleaning & manipulation.