BioBlocks: Programming Protocols in Biology Made Easier

Abstract

The methods to execute biological experiments are evolving. Affordable fluid handling robots and on-demand biology enterprises are making automating entire experiments a reality. Automation offers the benefit of high-throughput experimentation, rapid prototyping, and improved reproducibility of results. However, learning to automate and codify experiments is a difficult task as it requires programming expertise. Here, we present a web-based visual development environment called BioBlocks for describing experimental protocols in biology. It is based on Google's Blockly and Scratch, and requires little or no experience in computer programming to automate the execution of experiments. The experiments can be specified, saved, modified, and shared between multiple users in an easy manner. BioBlocks is open-source and can be customized to execute protocols on local robotic platforms or remotely, that is, in the cloud. It aims to serve as a de facto open standard for programming protocols in Biology.

Interactive programming paradigm for real-time experimentation with remote living matter

“…Consequently, cloud laboratories to remotely experiment with biological specimens have been developed and deployed for academia and industry (10), with applications including citizen science games (11, 12) and online education (13–16). Different approaches have been taken to make automated wet laboratory instruments programmable: Roboliq (17) uses artificial intelligence (AI) to ease the development of complex protocols to instruct liquid-handling robots; BioBlocks (18) and Wet Lab Accelerator (10) are web-based visual programming environments for specifying instrument protocols on cloud laboratories like Transcriptic (10).…”

Galaxy-SynBioCAD: Automated Pipeline for Synthetic Biology Design and Engineering

“…Additionally, there are already Galaxy workflows to take up and analyze metabolomics flow cytometry data in the ToolShed 34 , and these workflows could directly be incorporated into the portal to deal with data generated in the 'Test' step of the synthetic biology Design-Build-Test-Learn (DBTL) cycle. As mentioned in the introduction several open-source software products deposited in GitHub [26][27][28]44 could address the 'Build' step and eventually provide drivers to automated constructions using different robotic workstations beyond those provided by Opentrons. Regarding the 'Learn' step in DBTL, the OptDoE tool could easily be adapted to propose new designs as it was done in Carbonell et al 25 .…”

Small Universal Bacteria and Plasmid Computing Systems

“…Using such conjugation, DNA molecules, acting as information carriers, can be transmitted from one cell to another. On the basis of the communication, information in one bacteria can be moved to another and can be used for further information processing [ 5 , 6 ].…”