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About us

Partner institutes of EATRIS-CZ provide expertise and infrastructure for various types of analysis as well as for acquisition, storage and distribution of complex datasets. Experienced staff members can offer an overlapping expertise in IT infrastructure, programming, web/database management, data mining, statistics, bio/cheminformatics and can consult and assist in study design, implementation, and analysis, or develop new software tools to support your research activities. In addition to standard equipment and common software resources, computing infrastructure of the EATRIS-CZ institutes includes current generation of cluster, which is composed of 43xCPU nodes with Intel Xeon E5-2650 (2x in each node) and 20xGPU nodes with Nvidia Tesla M2090, totally 2016 logical CPU cores, 24x 300 GB + 276x 3TB.


Support of research/drug development projects

  • Preparation of design of clinical trials and laboratory experiments (determine sample size, specify analysis plan)
  • Conduct statistical analyses and provide statistical support to researchers in appropriate reporting of results
  • Perform virtual screening of your libraries with proprietary models predicting cytotoxicity
  • Drug design and in silico optimization of compound properties, e.g. ADME, off-target activity, etc. using various computational tools (machine learning, pharmacophore, molecular docking, molecular dynamics, etc.)
  • Provision of expertise on the collection, organization, analysis and interpretation of genomic, proteomic and other biological data
  • Provision of cheminformatics support for high-throughput screening program including annotation of compounds in the library, analysis of structure-activity relationships and identification of mechanism of action

Available unique software tools and databases

  • ClinData - software solution for collecting of clinical and laboratory data on patients included in various research projects and clinical studies (see https://clindata.imtm.cz).
  • PreClinData - software solution for collecting and statistical analyses of preclinical data included in various research projects. (see https://preclindata.imtm.cz).
  • MedChemBio portal of medicinal and biological chemistry (see http://medchembio.cz/)
  • Claire — system for reliable detection of protein variants from tandem mass spectra of proteome (see https://claire.imtm.cz/)
  • Decryptor — web-accessible software for identification of mutant and polymorphic proteins from standard MS/MS data (see http://decryptor.imtm.cz/)
  • SPCI – software for automated building, validation and interpretation of quantitative structure-activity relationship models (https://github.com/DrrDom/spci)
  • Psearch – software for automated building and validation of 3D ligand-based pharmacophore models (https://github.com/meddwl/psearch)
Design of clinical trials and laboratory experiments

Planning clinical trials and laboratory experiments including randomisation, sample size calculation and power analysis based on defined outcomes, measurements, hypotheses and possible confounders.

Complex statistical analysis

Statistical analyses of various type of measurements - laboratory results, clinical data, surveys, omics data, from exploratory data analysis to complex predictive models. Support in appropriate reporting of results (statistical consulting).

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