BioXM™ Knowledge Management Environment

BioXM-Knowledge

We define knowledge management as managing and analyzing complex information to generate intelligent strategic and operational decisions.

We provide organizations with knowledge that becomes an asset – an asset that is used to build scientific and business models – leading to better decisions, better strategies and a high ROI.

Turning knowledge into an asset.

The BioXM™ Knowledge Management Environment supports a unique process to build highly custom solutions by configuration not through classical software development. This paradigm shift enables rapid development at reduced cost driven by the research and business needs. This ensures that the solution is by design continuously adaptable to the changing requirements in the life sciences industry.

Click for more screenshots and full-sized images.bioxm-screenshot

Flexible BioXM™ technology drives knowledge management toward your needs enabling you to do the following:

  • Expand knowledge — semantically integrate any data from any source seamlessly
  • Refine decision making — connect the dots explaining systems
  • Create new hypotheses — visualize novel relationships between data networks

Applications using the BioXM™ platform:

  • Connect clinical data and statistical analyses.
  • Keep repositories of scientific data such as experimental results, a corporate gene index, a phenotype catalog, a patient register or a compound database.
  • Keep track of ongoing projects with one click to generate table reports and overview graphs.
  • Generate networks from multiple sources in one step and find previously undetected links in the data.
  • Identify biomarker candidates based on automated literature analysis and compare the results to experimental results in the same software platform.
  • Organize, review, compare, annotate and modify biological pathways originating from different sources.
  • Classify biological functions using ontologies specific to focused scientific areas.
  • Easily integrate external statistical packages (R, BioConductor), bioinformatics tools, chemoinformatics algorithms, Web services and more.
  • Empower end users — easily “tune” the user interface and manage knowledge using a standard web browser

Click to see a graphical representation of how BioXM works.
Then contact us at to set up a free consultation or set-up a demo.

References

  • Tissue banking, bioinformatics, and electronic medical records: the front-end requirements for personalized medicine.
    Suh, K. S., Sarojini, S., Youssif, M., Nalley, K., Milinovikj, N., Elloumi, F., et al.
    Journal of oncology, 368751 (2013) Abstract
    Full text
  • Toward an integrated knowledge environment to support modern oncology.
    Blake PM, Decker DA, Glennon TM, Liang YM, Losko S, et al.
    Cancer J. 5:38 (2011) Abstract Abstract
  • Knowledge management for Systems Biology: a general and visually driven framework applied to translational medicine.
    Maier D, Kalus W, Wolff M, Kalko S G, Roca J, et al.
    BMC Systems Biology 5:38 (2011) Abstract
    More information about the BioBridge Project
  • MeDALL (Mechanisms of the Development of ALLergy): an integrated approach from phenotypes to systems medicine.
    Bousquet J, Anto J, Auffray C, Akdis M, Cambon-Thomsen A, Maier D, et al.
    Allergy (2011) Abstract
    More information about the MeDALL project
  • Aus der Forschung an das Krankenbett
    Dieter Maier
    Systembiologie.de, Vol 02: 72-75 (2010)
    Full text
  • Ovarian cancer biomarkers for molecular biosensors and translational medicine
    K Stephen Suh, Sang W Park, Angelica Castro, Hiren Patel, Patrick Blake, Michael Liang and Andre Goy
    Expert Review of Molecular Diagnostics, Vol 10 (8): 1069-1083 (2010) Abstract
  • Finding Promising Protein Biomarkers
    Catherine Shaffer
    Genetic Engineering & Biotechnology News, Vol 30 (16): (2010) Original article
    Complete article for printing
  • Creating a Bridge between Modelica and the Systems Biology Community
    Jan Brugard, Daniel Hedberg, Marta Cascante, Gunnar Cedersund,Alex Gomez-Garrido, Dieter Maier, Elin Nyman, Vitaly Selivanov and Peter Stralfors Jan Brugard et al.
    Proceedings 7th Modelica Conference Como, Italy, Sep. 20-22, 2009
    Full text
  • Chapter 13: Semantic Data Integration and Knowledge Management to Represent Biological Network Associations
    Sascha Losko and Klaus Heumann Abstract
    in Protein Networks and Pathway Analysis
    Series: Methods in Molecular Biology , Vol. 563 (2009)
    Nikolsky, Yuri; Bryant, Julie (Eds.)
    Springer
    Table of contents
  • Functional Modules integrating essential cellular functions are predictive of the response of leukaemia cells to DNA damage.
    Sameith K, et al.
    Bioinformatics Advance Access, published online on September 17, 2008 Abstract
  • Integration of transcriptomics data into systems biology modeling in the BioBridge portal.
    Gómez-Garrido A, et al.
    CCIS Series 2008
  • Modeling and exploration of biological networks using the BioXM Knowledge Management Environment.
    Ilgenfritz H, Kalus W, Heumann K and Losko S
    Presented at International Symposium on Networks in Biology. Amsterdam, The Netherlands (2007)
    Full text
  • Knowledge Networks of Biological and Medical Data: An Exhaustive and Flexible Solution to Model Life Science Domains.
    Losko S, Wenger K, Kalus W, Ramge A, Wiehler J and Heumann K
    Lecture Notes in Computer Science 4075: 232-239 (2006) Abstract
  • Integration of biological data using BioXM Knowledge Management Environment.
    Ramge A, Losko S and Heumann K
    Presented at Bioinformatics Munich: from Genomes to Systems Biology Workshop Munich, Germany (2006)