Genedata

Genedata provides bioinformatics enterprise software solutions and a variety of software-related services that support large-scale, experimental processes in life science research - with a focus on automating data rich, highly complex data workflows. Genedata solutions are used in R&D laboratories primarily in biopharmaceutical but also in industrial and agro-biotech, nutrition, and health industries as well as in contract research organizations (CROs) and academic research institutions. The world's top 25 pharmaceutical companies license one or more of Genedata products or services, and the firm has relationships with more than 40 of the top 50 pharmaceutical companies.[1] The company is headquartered in Basel, Switzerland with subsidiaries and offices in Boston, London, Munich, San Francisco, Singapore, and Tokyo.

Genedata
Private
IndustryBioinformatics, Life Sciences
Founded1997
HeadquartersBasel, Switzerland
Area served
Basel, Switzerland
Boston
London
Munich
San Francisco
Singapore
Tokyo
Key people
Othmar Pfannes CEO
ProductsSee detailed listing
Number of employees
200+
Websitewww.genedata.com

Products

Genedata was founded in 1997 to address the evolving biopharmaceutical industry's data analytics needs. Since that time, the company has developed and continues to develop the following product platforms, which align with major R&D workflows to meet a range of research requirements (initial release dates are provided as well below):

  • 2002: Genedata Screener- for analyzing, visualizing, and managing screening data from any in-vitro screening assay technology[2].
  • 2005: Genedata Phylospher - for analyzing and managing target-discovery related data.
  • 2007: Genedata Biologics - for integrative workflow support in antibody screening, protein engineering, and biotherapeutics production.[3]
  • 2008: Genedata Expressionist - initially for the analysis and management of omics data such as mass spectrometry-based proteomics and metabolomics data[1] - today primarily for the characterization of biotherapeutics based on mass spectrometry.
  • 2010: Genedata Analyst - initially a standalone product for the integrative statistical analysis of large-scale experimental data in life science R&D, today used as integrated module of the Genedata Expressionist, Genedata Profiler, and Genedata Selector platforms.
  • 2010: Genedata Selector - for the analysis and management of genome-related data in the context of strain, cell line, and germplasm optimization.
  • 2015: Genedata Profiler - for the regulatory-compliant genomic profiling of patients in the context of clinical study optimization
  • 2016: Genedata Bioprocess - for integrative workflow support in bioprocess development from early cell line screening to downstream process and analytical development
  • 2018: Genedata Imagence - for automating and accelerating the analysis of phenotypic high-content images using deep learning.[4][5]
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gollark: rustc is quite slow. ghc, however, is fairly fast. The implications are obvious.
gollark: rustc is to be rewritten in Haskell for greater performance.
gollark: Wondrous.
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See also

References
  1. "SCW_APRMAY16". content.yudu.com. Retrieved 2019-03-01.
  2. "SCW_FEBMAR16". content.yudu.com. Retrieved 2019-03-01.
  3. "Data-Driven Cell-Line and Process Development | GEN - Genetic Engineering and Biotechnology News | Page 5137". Retrieved 2019-03-01.
  4. Walter, Kenny (2019-01-16). "Deep Learning Software Speeds Up Drug Discovery". Research & Development. Retrieved 2019-03-01.
  5. "Bio-IT World". www.bio-itworld.com. Retrieved 2019-03-01.
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