Meet our Founder!

We had a little Q&A session with our founder A/Prof Anthony Bosco to find out what motivated him to start INSiGENE and to pick his brains on various topics around Omics data. Here's what he had to say:

Tell us about more about yourself and why you started INSiGENe.

I am an Associate Professor of Immunobiology with expertise in Systems Biology.

We started the company because we realised that there was a shortage of Bioinformatics experts who know how to get the most out of your data. At INSiGENe, we have built a multidisciplinary team that specialises in extracting disease biology and mechanistic insights from omics data.

We also noticed that lots of young scientists are leaving academia due to lack of funding and limited opportunities for career development. INSiGENe provides employment for data scientists who love doing science but do not want to spend all their time applying for grants. ?

How do you see the field of omics data analysis evolving in the next few years?

The field will be advanced through the development of novel technologies and data analysis methods that enable a much deeper understanding of the cellular and molecular mechanisms and their dynamic states that drive processes across multiple omics layers, within and between multiple organ systems at single cell resolution.

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What challenges do you think researchers currently face in the analysis of omics data, and how can these challenges be addressed?

Data reproducibility is clearly very important, and there are specific tools already present which can address that. I also think data interpretation is currently a huge bottleneck. Extracting meaningful insights from vast multi-dimensional data sets is the main challenge for bioinformaticians and basic scientists.

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Can you discuss some recent breakthroughs in the analysis of large-scale omics data sets, and how they are impacting the field?

An important conceptual advance in the field of omics data analyses is the growing understanding that complex traits and diseases are influenced by the combined effects of thousands of genes, each contributing in a small way. This has paved the way for the development of a tool called polygenic risk scores, which combines information across many genes to predict an individual's risk of developing a disease.

When viewed through a Systems biology lens, emerging evidence suggests that the mechanisms that determine health versus disease are more related to subtle changes in the topology and connectivity structure of biological networks, along with their dynamic states. According to this systems-level view of disease, the current approach in drug discovery which targets individual factors is no longer considered effective.?

What role do you see machine learning and artificial intelligence playing in the analysis of omics data, and what are some of the most promising applications in this area?

?AI will enhance every step involved in the analysis and interpretation of omics data. For example, it is impossible for a human to read the totality of the vast biomedical literature. AI can do this and summarise it at lightning speed, accelerating the interpretation of experimental data.

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Can you discuss some of the emerging trends in multi-omics data integration and analysis, and their potential impact on clinical applications?

The application of multi-omics and data integration was crucial in understanding the inflammatory mechanisms that determine the pathogenesis of severe covid versus mild covid.

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How do you think the incorporation of newer technologies such as single-cell sequencing and spatial transcriptomics is transforming omics data analysis?

Disease processes occur in tissue microenvironments and are mediated by complex and dynamic cellular interactions in local niches that are governed by signaling events and gradients. Spatial transcriptomics at single cell resolution will enable for the first time the unbiased study of these mechanisms.

Can you discuss some of the ethical considerations and challenges associated with the analysis and interpretation of omics data in the context of personalised medicine and precision health?

Newborn screening is growing in popularity and is great for early disease diagnosis, but may be problematic if applied to other physiological traits. Aging and longevity research whilst interesting could create unforeseen problems if interventions are rolled out at scale.

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How do you see the integration of omics data with other types of health data (such as electronic health records) evolving in the coming years?

Integrating omics into healthcare will enable the identification of early warning signals that precede the onset of disease. This will enable the timely application of pre-emptive actions that can revolutionise healthcare through disease prevention.?

Finally, what advice would you give to young researchers who are interested in pursuing a career in the field of bioinformatics and omics data analysis?

My advice would be to join a large multidisciplinary collaborative team that has a critical mass of basic scientists and clinicians, secure funding, and is working on an important problem that has a long-term vision to have an impact!