Software Engineering

The Software Engineering team combines commercial software implementation with custom made tools and algorithms to support the Center’s cutting-edge research and development.

The team is comprised of bioinformaticians and software engineers and focuses on the implementation, development, and support of software products to fulfil the needs of our researchers. 

 

The team always conducts a thorough build-versus-buy assessment of various commercial products to identify the best solutions for streamlining lab workflows and enabling the capture of research data that can be searched, aggregated and analysed. The team applies an innovative product development methodology that combines the practices of design thinking and agile development.

 

This combination promotes focusing on problem analysis to ensure we “build the right things” that align with actual needs, and then focusing on “building it right” to deliver quality solutions that will increase adoption rates by end-users.

 

This team develops, and supports, the following applications:

 

1. Benchling – a leading commercial cloud-based LIMS (Laboratory Information Management System) comprised of an ELN (Electronic Lab Notebook) integrated with a registry, storage and request system. The ELN allows scientists to capture both structured and free-form data and develop templates for common experiments to ensure adherence to standard protocols. The inventory system enables detailed tracking of high value items, such as strains, and includes custom barcoding. The request system enables users to submit samples for processing by various service groups, track the status of their samples and seamlessly get back the results when available. Large experiments can be streamlined using the lab automation runs and workflows, finishing off with a graphical SQL module that allows users to retrieve data and graphs that summarise their work.

 

2. Custom LIMS (Benchling) Extensions – a custom extension to our commercial software Benchling, which includes a strain lineage browser to allow users to have a graphical view of their strains and cells, to filter and plan the next steps in their research. It also includes exports and parsers to improve the data flow, as well as a customised sample submission process to fit our individual R&D needs.

 

3. Enterprise search - a search and analytics engine that supports full text search, literature mining and integrates our internal data with public databases. The tool finds the desired keywords, or full text sentences, within levels of your ELN entries, ELN Attachments and Strain Registry. Complex data spread through several experimental SOPs, ELNs and entities are scanned to provide a compact list of possibilities, minimising clicking and manual search. Experimental data becomes easily accessible and sharable within the group without requiring a pinpoint to the metadata. This module also includes a directory of data assets that were created at the international sections.

 

4. Asana – a commercial task and productivity tool, designed to help teams organise, track and manage their work. Provides everything needed to stay in-sync, hit deadlines and reach goals.

 

5. Exputec - a Bioprocess Data Management, Data Analytics and Statistical Consulting tool. It helps to accelerate the development of bioprocesses and provides capabilities in data management, data analysis and statistical reporting. One of the extensions being developed is an integration with the Exputec software. We allow users to export an Exputec compatible file containing all their raw data collected during the experiment. This file is then imported into our Data Warehouse.

 

6. Metabolic Model Reconstruction – this module enables researchers to collaborate on the reconstruction of metabolic models with identifier standardisation.

 

7. Pathway Prediction (GemPath) – a retrosynthetic-based pathway prediction algorithm providing a comprehensive search of the biochemical space.

 

8. Global Atlas (Escher) – a web application for visualising metabolic pathways. Rapidly create pathway visualisations, contextualise omics data and simulations (RNA-Seq, proteomics, flux data, etc.) and generate high-quality images for sharing results.

Contact

Vincenzo Capuano
Director Software and Data Architecture
DTU Biosustain
+45 93 51 09 21