Knowledge Management Environment

The BioXM™ Knowledge Management Environment is a fully customizable, all-in-one enterprise knowledge management system for better integrated, evidence-based research and development.

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    The BioXM platform provides a central inventory of all the information representing an organization’s collective knowledge. While individuals focus on generating knowledge in their specific fields of expertise, the whole organization can benefit from that knowledge to make better decisions and follow more intelligent strategies.

    The BioXM platform allows quick configuration of highly customized solutions that are driven by specific research and business needs. The knowledge model can continuously adapt to new information or circumstances, which leads to more agility in the face of change, a higher ROI, and ultimately more stability and success.

    Your benefits

    Your Benefits

    The possibilities are virtually limitless. The following are only a few examples.
    • Connect and explore clinical data, study information and statistical analyses
    • Keep non-redundant repositories of scientific data such as: experimental results, a corporate gene index, a patient register, a phenotype catalog, or a compound and drug database
    • Create comprehensive disease maps based on automatic literature mining results
    • Connect, organize, review, compare, annotate and modify biological pathways originating from different sources
    • Identify biomarker candidates based on automatic literature analysis and compare the results to experimental findings in one platform
    • 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
    • Generate networks from multiple sources and find previously undetected links in the data
    • Keep track of ongoing projects with one click to generate smart folders, table reports and overview graphs

    More details

    Consolidate knowledge

    The BioXM system is a project-centered, distributed platform that allows isolated sources of information to be connected into a central inventory of information and knowledge.

    Users create, manage and visualize scientific models as extendible networks representing an area of research or a particular perspective.

    Reveal hidden relationships

    The BioXM platform is configured to the way real users work and real projects develop. It connects the dots between the data and the people behind the data.

    Through semantic modeling of interrelated concepts, all perspectives are integrated into the knowledge network and relationships that were previously hidden become clear.

    Leverage many perspectives

    Personalized user interfaces and flexible access support diverse users and project groups.

    Individuals can focus on their science and generating knowledge in their field of expertise while the whole organization can deploy it to gain insight, make better decisions and innovate faster.

    Connect all resources

    The BioXM platform integrates seamlessly into diverse computing environments and ensures secure and efficient data sharing among team members within distributed environments.

    The whole organization benefits from connecting all data, tools, people and processes.

    Ensure future agility

    The BioXM platform can be used to build highly custom solutions through configuration rather than classical software development.

    This novel process enables faster, less expensive development driven by real research and business needs.

    A solution based on the BioXM platform can, by design, continuously adapt to changing requirements.

    Empower end users

    The BioXM system can be used to create browser-based web apps that dynamically access the semantic knowledge network on any device.

    In this way, easy-to-use frontends can be created to ensure that any kind of user — from novice to expert — can contribute to and benefit from the organization’s collective knowledge.


    The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research
    Cano I, Tényi Á, Schueller C, Wolff M, Huertas Migueláñez MM, Gomez-Cabrero D, Antczak P, Roca J, Cascante M, Falicani F and Maier D (2014) Journal of Translational Medicine 12(Suppl 2):S6
    Abstract | Full text | More information about the Synergy-COPD project

    Tissue banking, bioinformatics, and electronic medical records: the front-end requirements for personalized medicine.
    Suh KS, Sarojini S, Youssif M, Nalley K, Milinovikj N, Elloumi F, et al. (2013) Journal of Oncology 368751
    Abstract | Full text

    Toward an integrated knowledge environment to support modern oncology.
    Blake PM, Decker DA, Glennon TM, Liang YM, Losko S, et al. (2011) Cancer Journal 5:38

    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. (2011)BMC Systems Biology 5:38
    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. (2011) Allergy
    Abstract | More information about the MeDALL project

    Aus der Forschung an das Krankenbett (From research to bedside)
    Dieter Maier (2010) Vol 02: 72-75
    Full text

    Ovarian cancer biomarkers for molecular biosensors and translational medicine
    Suh KS, Park SW, Castro A, Patel H, Blake P, Liang M and Goy A (2010) Expert Review of Molecular Diagnostics Vol 10 (8): 1069-1083

    Finding Promising Protein Biomarkers
    Shaffer C (2010) Genetic Engineering & Biotechnology News Vol 30 (16)
    Original article | Complete article for printing

    Creating a Bridge between Modelica and the Systems Biology Community
    Brugard J, Hedberg D, Cascante M, Cedersund G, Gomez-Garrido A, Maier D, Nyman E, Selivanov V and Stralfors P (2009) Proceedings 7th Modelica Conference Como, Italy
    Full text

    Semantic Data Integration and Knowledge Management to Represent Biological Network Associations
    Losko S and Heumann K (2009) in Protein Networks and Pathway Analysis Table of contents
    Nikolsky Y, and Bryant J (Eds.) Series: Methods in Molecular Biology Vol. 563 Springer

    Functional Modules integrating essential cellular functions are predictive of the response of leukaemia cells to DNA damage.
    Sameith K, Antczak P, Marston E, Turan N, Maier D, Stankovic T and Falciani F (2008) Bioinformatics 24(22):2602-7

    Integration of transcriptomics data into systems biology modeling in the BioBridge portal.
    Gómez–Garrido A, Márquez S, Hernández M, Selivanov V, Cascante M, Villà–Freixa J and Kalko S (2008) in Schriftenreihe Informatik 26. BIRD08 2nd International Conference on Bioinformatics Research and Development. pp. 75-81

    Modeling and exploration of biological networks using the BioXM Knowledge Management Environment.
    Ilgenfritz H, Kalus W, Heumann K and Losko S (2007) Presented at International Symposium on Networks in Biology.Amsterdam, The Netherlands
    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 (2006) Lecture Notes in Computer Science 4075: 232-239

    Integration of biological data using BioXM Knowledge Management Environment.
    Ramge A, Losko S and Heumann K (2006) Presented at Bioinformatics Munich: from Genomes to Systems Biology Workshop Munich, Germany

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