Department of Medical Statistics, University Goettingen

KNIMEDataProcessingWorkflow

Learn to Use KNIME - a graphical workflow mananager

An introduction to reproducible handling of scientific data and concordant analysis using KNIME workflows


The Core Facility Medical Biometry and Statistical Bioinformatics and the CandActCFTR project are jointly conducting an introductory course on preprocessing, analysing data using KNIME Workflows.

course frame:

block seminar: 2 afternoons @ CIP room, UMG - Department of Medical Statistics

target group:

people working with data tables, interested in getting an overview of their data, who want to easily select subsets from bigger cohorts or have to bring together information from multiple data table sources into one analysis.

potential gain:

knowing what to collect and how it should be organized / formatted: from pile to structured database.
aquire usefull tricks to monitor progress during data collection, and to streamline / focus data collection toward analysis.
easier formating and joining of input data from different sources towards an actual analysis task.

gain of using KNIME

knowledge about a versatile free software tool, which is operating system independent.

software source:

freely available here: KNIME

This course has two main aims:

learning goals:

day 1
The participants should be able to:
in general
use input / output
join tables
perform data selection
do data analysis / derive statistics
day 2

do advanced data analysis / deriving statistics
create advanced output
exemplary course data set:
is a use-case applied to processing of a typical literature search task (PubMed results list) to the concurrent similarity analysis and subsequent adding of more information from data sources like ChEMBL

next Dates & time line

  • Day 1: 2018-11-05, Monday, 13:00-18:00 h
  • Day 2: 2018-11-06, Tuesday, 13:00-18:00 h

Speakers

  • Manuel Nietert (PhD) : CandActCFTR project

Language

  • English

Limited seats available, preference based on first-come-first-served.

Location

Computer pool at the institute of medical statistics

Humboldtallee 32, ground floor

Map

Prerequisites

  • none

Registration

Prefered is the use of Stud.IP
or in case you do not have an studip account please send an email to manuel.nietert@med.uni-goettingen.de.