We simplify the functioning of genomics pipelines

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The roots of MNM go back to the world of science, where sharing knowledge is essential.

When academics openly publish the results of their research as soon as possible, then the whole science community reacts, and provides feedback or debate. This amazing mechanism assures constant development and self-regulation of mainstream science.

In the software development world, this mechanism - sharing information and collaborative improvement of software code also has a long history, essentially as long as software development itself. This is known as free open-source software, which allows anyone using the code to maintain and modify the code.

In MNM Bioscience, we support that culture of sharing, which is why our latest software-the NeKO component, will be released on an open-source licence. Open source has revolutionized data engineering and data science. An interesting example of such software is the Hadoop ecosystem and Spark engine (Spark is considered the successor to the Hadoop MapReduce model.) From the history of the Hadoop project, we know that there were two important papers openly published by Google (The Google File System and MapReduce: Simplified Data Processing on Large Clusters). Google publicly released its research, and thus contributed to the launch of the Big Data revolution. As a result, we can use Spark today at MNM to identify and rate our drug targets. Google and other tech giants contributing to open source software and sharing their research results in changing various aspects of human life. We want to be part of this process.

Within the landscape of computational science, NeKO operates “where the rubber hits the road” – it bridges the gap between the scientific pipeline ecosystem (Nextflow) and cloud computing orchestration (Kubernetes) by providing an intermediate layer, seamless to the end user.

NeKO enables launching of the Netflow pipeline in a declarative manner on top of the Kubernetes cluster. Thus, NeKO takes the burden of the configuration, scheduling, and maintenance of computational pipelines off the scientific teams’ shoulders, allowing them to work in a cloud-native environment without the need for support from dedicated IT specialists.

We simplify the functioning of genomics pipelines
October 13, 2022

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