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BigOmics Analytics

BigOmics Analytics
Business Name: BigOmics Analytics
Founders: Dr. Murodzhon Akhmedov (CEO) and Dr. Ivo Kwee (CTO). Both the two founders hold a PhD and have solid backgrounds in bioinformatics, programming and artificial intelligence, which are essential for the continuous development and maintenance of the platforms. In addition, Dr. Akhmedov also has an academic background in management to carry out business development activities.
Business Genre:
Why are you launching the business? What "problem" are you addressing? : The vast amount of genomics data being currently generated hold the key for finding new cures for many diseases, including cancer and autoimmune disorders. By unlocking this knowledge, we can improve lives through more accurate diagnosis of diseases, development of personalized treatments, and monitoring the efficacy of therapies. As sequencing costs keep decreasing, the bottleneck to make effective use of omics data and solve clinical questions is gradually shifting from data availability to data analysis. However, a major dilemma exists: in many cases biologists, who best understand their experimental data, lack the computational background to effectively analyze them and often are completely dependent on bioinformatics experts who are less familiar with the biological nature of experiments. Adding to that, the rapid growth of data generation is putting increasing demands on bioinformaticians to perform analysis, resulting in longer waits to deliver results.

Self-service analytics (SSA) promises a solution to this problem: SSA achieves end-user flexibility and scalability by enabling biologists to perform the analysis themselves. Several SSA sequencing analysis platforms and services are currently available. However, they tend to require advanced bioinformatic skills, unless their analysis is restricted only to the most basic functions in order to provide greater accessibility to unskilled users. The latter approach looks increasingly inadequate to satisfy the needs of most biologists.

The aim of BigOmics Analytics is to offer user-friendly platforms that do not require advanced bioinformatics knowledge to perform sophisticated, cutting edge analysis of omics data, thus bridging the current gap in SSA offerings.
How do you address the problem? What solution do you provide?: We address the problem by offering three platforms that provide easy access to vast amounts of public data, offer fast and advanced analytics, and are easy to use. These are: the Omics Playground, the RepSeq Playground and the Multiomics Playground. The three platforms address different needs in the field. The Omics playground is focused on providing not only advanced analysis features for gene expression datasets (including proteomics data), but, thanks to access to a large database compiled from publicly available datasets, also give user access to sophisticated meta-analysis. We have recently set up an open access version of the platform dedicated to viral infections to help scientists in the fight against the recent COVID-19 epidemic ( It includes more than 200 pre-loaded public datasets for analysis, including datasets from SARS-CoV-2, SARS, MERS and other viral infections. The RepSeq Playground emphasis on immunology-related analysis for the receptor repertoire sequencing data. It thus provides access to a distinct combination of features to explore, among others, expansions of clonal families over the time, multiple sequence alignments and generation of phylogenetic trees of single cell samples. Finally, the Multiomics Playground addresses the increased demand for the integration of omics data of various nature (e.g. transcriptomics, genomics, proteomics, metabolomics, etc.) by performing a machine learning driven meta-analysis of related omics datasets to gain novel molecular and biological insights.

All the three versions are constantly kept up-to-date to integrate the latest developments in the field.
What will be the benefit of your product? What will the world look like once it is launched?: With our platforms, we aim to democratize biodata analysis in digital health to accelerate scientific discoveries in medicine. The platforms would make analysis of omics data more accessible, faster and more efficient. This is achieved by providing analysis beyond simple pairwise comparisons to include access to large databases of sequencing datasets and comparative analyses across datasets that take full advantage of the current big data explosion. All this is achieved via a user-friendly and accessible interface that does not require specialized skills in programming or statistical analysis.

Through these platforms, biologists can become more independent when interpreting their datasets without sacrificing depth of analysis. This can also be of great benefit to bioinformaticians themselves, as integrating the platforms in their workflow would free up time for more creative and cutting-edge software development rather than being stuck in repetitive pipeline development and constant re-analysis due to biologists’ feedback. As a consequence, by facilitating and speeding up the time of omics data analyses, we help life-scientists (and, after the advent of personalized medicine, possibly clinicians) better understand several diseases and accelerate the identification and development (or repurposing) of treatments.
Business Address: Via Vela 6
Bellinzona, TI / Switzerland, 6500

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Listing Title: BigOmics Analytics