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Applied Computational Biology

The members of the Applied Computational Biology group at the IEG cover a wide range of scientific disciplines, all possessing deep IT knowledge and experience and a strong command of the IT toolbox. 

As a team, we work at the interface between biology and applied computer sciences in our institute as well as in external collaborations. 

The members of the Applied Computational Biology group at the IEG cover a wide range of scientific disciplines, all possessing deep IT knowledge and experience and a strong command of the IT toolbox. 

As a team, we work at the interface between biology and applied computer sciences in our institute as well as in external collaborations. 

About our Work

In our scientific branch, we initiate and take lead in projects that apply artificial intelligence methods on large mouse phenotyping datasets. We use internal data from the German Mouse Clinic (GMC) as well as external data from the International Mouse Phenotyping Consortium (IMPC) and other sources.

Such projects aim to

  • uncover so far unknown genome-phenome relationships and to identify new candidate genes for models of human disease
  • speed up or even enable data analysis in depths not possible so far
  • implement objective, unbiased data processing pipelines for the re-analysis of large phenotyping raw data collections
  • provide automated and powerful QC tools for the highly standardised GMC phenotyping pipeline. 

 

We develop and maintain highly customised IT infrastructure and IT solutions for our institute. The German Mouse Clinic runs a large collection of special hardware devices and software to measure and capture phenotyping data. Our in-house developed application "MausDB" is a modular laboratory information management system (LIMS) that integrates work planning as well as capture, management and analysis/visualisation of data, providing a high degree of automation [2,3]. Our team provides high-availability service of MausDB and all connected subsystems, as the GMC runs a clocked, time-critical high-throughput operation.
We are also responsible for management, integration, curation and quality control of GMC data using automated and manual procedures following our internal SOPs.
In a center-wide commitment, we have developed and continuously maintain a generic version of MausDB for animal facility management at >20 HMGU institutes, which enables automated and law-compliant generation of the "Jahresstatistik" according to VersTierMeldV and 2010/63/EU.

We internally support IEG research projects with our IT expertise and our tools. This involves, but is not limited to, performing custom SQL queries on our LIMS to extract specific project data, statistical consulting for experimental design and data analysis as well as development of custom big data processing and data analysis solutions, involving AI methods.

In our scientific branch, we initiate and take lead in projects that apply artificial intelligence methods on large mouse phenotyping datasets. We use internal data from the German Mouse Clinic (GMC) as well as external data from the International Mouse Phenotyping Consortium (IMPC) and other sources.

Such projects aim to

  • uncover so far unknown genome-phenome relationships and to identify new candidate genes for models of human disease
  • speed up or even enable data analysis in depths not possible so far
  • implement objective, unbiased data processing pipelines for the re-analysis of large phenotyping raw data collections
  • provide automated and powerful QC tools for the highly standardised GMC phenotyping pipeline. 

 

We develop and maintain highly customised IT infrastructure and IT solutions for our institute. The German Mouse Clinic runs a large collection of special hardware devices and software to measure and capture phenotyping data. Our in-house developed application "MausDB" is a modular laboratory information management system (LIMS) that integrates work planning as well as capture, management and analysis/visualisation of data, providing a high degree of automation [2,3]. Our team provides high-availability service of MausDB and all connected subsystems, as the GMC runs a clocked, time-critical high-throughput operation.
We are also responsible for management, integration, curation and quality control of GMC data using automated and manual procedures following our internal SOPs.
In a center-wide commitment, we have developed and continuously maintain a generic version of MausDB for animal facility management at >20 HMGU institutes, which enables automated and law-compliant generation of the "Jahresstatistik" according to VersTierMeldV and 2010/63/EU.

We internally support IEG research projects with our IT expertise and our tools. This involves, but is not limited to, performing custom SQL queries on our LIMS to extract specific project data, statistical consulting for experimental design and data analysis as well as development of custom big data processing and data analysis solutions, involving AI methods.

Group Members

Elida Schneltzer

Group Leader of Applied Computational Biology View profile

Isabella Galter

Doctoral Candidate

Dr. Christoph Lengger

Research Data Manager

Dr. Holger Maier

Senior Data Scientist

Pragya Mishra

Computational Biologist

Manuela Östereicher

Statistician

Christine Schütt

IT-Scientist

Dr. Ralph Steinkamp

Lilly Zapf

Data Manager

Selected Publications of the Group

Contact

Elida Schneltzer

Group Leader of Applied Computational Biology

Building 35.14, Room 133