Medical Systems Biology

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Praktische Algorithmen der Bioinformatik und Computerlinguistik mit Lisp

 

 

Dozent:    
Dr. Ludwig Lausser
 
Dr. Johann Kraus
Dr. Markus Maucher
Dr. Tilman Becker
Dipl.-Inf. Gunnar Völkel
Prof. Dr. Hans A. Kestler     

Code:

CS8095.000

 

 

 

 

 


Vorlesungszeiten und Ankündigung

  • Kompaktkurs
  • Blockverantstaltung: 26. bis 29. März 2018, voraussichtlich jeweils von 08:30 - 17:00 Uhr, Raum O27 / 2201 (Beginn: Montag, 26. März, um 8:30 Uhr)
 

Inhalt und Themen

Die Veranstaltung vermittelt Algorithmen der funktionalen Programmierung in Lisp im Hinblick auf die Anwendungsgebiete Bioinformatik und Computerlinguistik.

 

Latest News

 

Congratulations to Dr. Silke Werle for winning the 1st Prize with her pitch at the 1. Science Day held by ProTrainU. 

 

Our paper "Reconstructing Boolean network ensembles from single-cell data for unraveling dynamics in the aging of human hematopoietic stem cells" has been published in the Computational and Structural Biotechnology Journal.

 

The position paper "Is there a role for statistics in artificial intelligence" has been published online first in Advances in Data Analysis and Classification.

 

Our paper "Corona Health - A Study- and Sensor-Based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic" has been published in the International Journal of Environmental Research and Public Health.

 

Our paper "Patient empowerment during the COVID-19 pandemic: Ensuring safe and fast communication of test results" has been published in the Journal of Medical Internet Research.

 

Our paper "Perspective on mHealth Concepts to Ensure Users’ Empowerment–From Adverse Event Tracking for COVID-19 Vaccinations to Oncological Treatment" has been published in IEEE Access.

  

Our report protocol "Digitalization of adverse event management in oncology to improve treatment outcome—A prospective study protocol" has been published in PLoS One.

 

We are happy we could contribute to Beutel et al (2021) "A prospective Feasibility Trial to Challenge Patient-Derived Pancreatic Cancer Organoids in Predicting Treatment Response" published in MDPI Cancers.