Computation Modeling

We improve our computational modeling and experimental design through a continuous process.

At Fornia BioSolutions, we apply advanced in silico modeling tools, as well as the most current systems biology information, to guide the engineering of microorganisms. We utilize in silico modeling (computational models of biology) and computational simulations for quantitative analysis at the gene-to-genome-levels.

Our Laboratory Information Management System (LIMS) has been developed in-house. It is a software-based system, with features that support every step of our workflow. Key features include – but are not limited to: project management, gene/strain management, gene/strain library management, plate management, test management and sequence management. Our LIMS plays a key role in scheduling, tracking, analysis and reporting of R&D work.

After a large amount of high-throughput, experimental data is generated and fed into our proprietary LIMS, the data can be conveniently exported, as desired, by our data scientists. It can then be used for applying suitable and reliable machine learning algorithms. The goal is to uncover hidden insights, such as the effect of changing sequences, genetic constructs and pathways, on strain functions of interest. Learning from relationships, trends and patterns in the historical data, helps produce effective decisions and results. Our computational modeling and experimental designs are improved in a continuous process, which develops production strains that are competitive and optimal for industrial applications.

System-level engineering of microorganisms can be accomplished by the integration of in silico and wet lab experiments. Recent advances in high-throughput experimental and bioinformatics techniques have led to the rapid accumulation of a broad range of “-omics” data (i.e.: genomics, transcriptomics, proteomics, metabolomics, fluxomics and so on).

If you are interested in learning more about our Computation Modeling, please call Fornia BioSolutions Inc. at 510-264-0183 or email us at