Genialis Releases Improved Version of Expressions for Faster, More Secure Multi-Omics Processing and Data Management

Cloud software for bioinformatics and systems biology is relaunched with an eye toward speed and fortified ISO 27001 compliance

Genialis, a leader in applied data science for the development of precision medicines, announced an update to Expressions(™), the FAIR-inspired data management and bioinformatics processing software suite, to make analyzing and querying data faster, smarter and safer. With this new release, Genialis has dramatically improved the software for NGS data processing, management and visualization by increasing analysis speed and computational efficiency. Genialis has further added to the completeness of the underlying knowledge base and library of validated multi-omics pipelines. All improvements are aligned with the goal of improving security and maintaining Genialis’ long-standing ISO 27001 certification.

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“Our ability to discover and develop precision medicines hinges on deciphering complex biological systems, and that depends on being able to integrate and interrogate the right types of data for the problem at hand”

Expressions serves as the foundation for Genialis’ computational precision medicine technology stack, fueling Responder ID, the patient-centric AI platform for modeling complex disease. In the latest version of Expressions, Genialis has implemented cloud-native, scientifically validated pipelines for miRNA-, methyl- and whole-genome sequencing analysis. The gene search functionality has also become more intuitive, thanks to improvements to the underlying knowledge base, including an update to Ensembl105 gene IDs. To enhance interoperability, Expressions now links directly with Open Targets to enable exploration of genes of interest with a vast amount of supplementary information, from molecular interaction and pathways to clinical drug precedence according to their curated mechanism of action. Additionally, existing security features and password requirements have been updated to the latest best practices.

Genialis has improved its Expressions software for NGS data processing, management and visualization by increasing analysis speed and computational efficiency. Genialis has further added to the completeness of the underlying knowledge base and library of validated multi-omics pipelines. All improvements are aligned with the goal of improving security and maintaining Genialis’ long-standing ISO 27001 certification. (Graphic: Business Wire)

“Genialis Expressions is well suited to the analysis of the many types of ‘omics data required to understand cancer biology,” said Taeko Inoue, Ph.D., Senior Scientific Project Manager at Genialis. “Researchers collaborating across institutions like Texas Children’s Hospital, Baylor College of Medicine, and St. Judes, for example, have benefited from the secure access and rich metadata annotations that Expressions affords.”

In just one example of Expressions’ computational efficiency, Genialis recently helped a biopharma partner process several thousand patient samples, each of which had data generated by WGS, mRNA, miRNA and methyl-seq. The WGS data alone constituted ~2.5 trillion short reads, 200 Tb of input raw data,1000 Tb (1 Petabyte) of total processed data, analyzed below the cost and time requirements of other considered solutions.

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“Our ability to discover and develop precision medicines hinges on deciphering complex biological systems, and that depends on being able to integrate and interrogate the right types of data for the problem at hand,” said Rafael Rosengarten, Ph.D., CEO of Genialis. “With the latest enhancements to Expressions, we can perform fundamental analyses even more securely and at a much greater scale. Genialis customers will also benefit from reduced cycle time at lower costs per data unit, and be on their way to making life-saving discoveries.”

Genialis is attending the 12th Clinical Biomarkers & CDx Summit Europe in London on April 27-28, where Dr. Rosengarten will moderate a panel titled “Incorporation of Artificial Intelligence into Clinical Development Strategy: Best Practices & Pitfalls.”

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