Science app development for a B2B client

User roles

• Researcher role

  Scientists and researchers upload molecular structure files and create research projects. They analyze sequences through tables and charts, explore 3D visualizations, and export data for their studies. The system handles their calculations while they focus on interpreting results.

• Project administrator role

  Since Proteineer operates as one of the B2B life science software solutions, project administrators manage user access and allocate computational resources for different research projects. They coordinate between the research teams and ensure proper distribution for the molecular calculations.

Key features

• Project-based organization

  The life science app structures work around individual research projects, with each project containing its own datasets and analysis results. This helps research teams manage multiple studies simultaneously.

  

• Molecular sequence processing

  Proteineer handles massive uploads of molecular structure files, processing sequences through intensive backend calculations. The life science app organizes results into navigable tables with smart pagination, letting researchers quickly locate specific sequences.

  

• Similarity analysis visualization

  The platform generates interactive charts showing relationships and correlations between different molecular sequences. Scientists can explore these connections through specialized network graphs, making complex data relationships immediately visible.

  

• Cherry-picking molecular sequences

  The platform enables selective extraction of high-value molecular sequences based on customizable criteria such as structural stability, functional relevance, or evolutionary conservation. Advanced filters and interactive visualizations highlight key attributes, streamlining the prioritization process for experimental validation or computational modeling.

  

• 3D molecular rendering

  Through Molstar integration, researchers can view detailed three-dimensional representations of molecular structures. This life science software feature allows side-by-side comparisons of selected molecules, helping analyze structural differences and similarities at the molecular level.

  

• Cluster analysis

  The system groups similar sequences into clusters, displaying these relationships through organized charts and tables. Researchers can quickly identify molecular families and patterns, streamlining the process of finding related compounds within large datasets.

  

• Data export capabilities

  Scientists can export their analysis results in multiple formats for external use. The platform maintains data integrity while providing flexible output options that integrate with other research tools and documentation workflows.

  

Business outcomes

The Proteineer web interface made it much easier for research customers to work with their molecular data. By building proper tables and charts, we solved the main problem scientists had — getting quick access to their analysis results. Researchers can now find what they need in seconds instead of dealing with messy data files.

Our science app development work helped the client offer a better service to universities and research institutions. The simple web frontend reduced support requests and made it easier for new users to get started. Scientists spend less time figuring out the interface and more time on actual research.

The 3D visualization and data organization features made Proteineer feel like a complete research tool, not just a number-crunching service. This helped the client stand out when competing for new institutional clients and strengthened the B2B relationships with institutions, expanding the customer base for new researchers.