Optofarmakológia - Új irány a gyógyszerkutatásban

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Science Intensive Software Development

At Printnet, we develop custom software that requires specific scientific knowledge. We are experienced in realizing projects that had been considered nearly impossible. Our secret lies in our strong links with Hungarian research institutes that allow us to employ the best specialists.

The Printnet team has already solved various extraordinary and tricky problems (often where other developers have failed) in the following areas of custom software programming:

  • Movement Analysisand Pattern Recognition

With our know-how in pattern and movement analysis we can track and recognize objects from mere camera images. These techniques can be applied to different types of scientific or business problems, ranging from the microscopic applications to biometric identifications.

  • Life Sciences

Unique experience gained in biochemistry and genetic projects, regular cooperation with science community and optimal combination of IT and Science in experts' skills help us to deliver outstanding and innovative IT solutions to pharma and life science companies worldwide. Our experience comprises drug discovery and drug reposition, we offer software solutions for chemistry and molecular modeling, fundamental bioinformatics problems, and pharmaceutical industry.  

  • Data Clustering

Starting from molecular biology problems, we developed our data clustering solutions. These softwares can be used even in grid environment (on multiple computers working together), and they can recognize not only separated, but overlapping data clusters. This knowledge could be extremely useful in data mining projects, where grouping the information can be tricky, and data groups cannot be determined before processing. Clustering could indentify formerly hidden groups for example in marketing or financial data warehouses.

  • Machine Learning and Classification

Our Neural Network based systems could extract and discover trends, patterns and tendencies hiding between the huge amount of data. Even when the exact mechanism of a process is not known, our network might be able to give some hints, or clues about possible outcomes. Just give us your problem and your data and our NN might deliver some decent predictions.