These are unique questions and answers not given in the podcast interview. I’m experimenting with this, and thankfully, Matt and Mathew decided to give it a try. See the full episode here with all of the hyperlinked timestamped show notes to navigate the audio.
About the Company:
Bioinformatics is a rapidly expanding, data-intensive field relevant to almost every aspect of the biosciences. At Blue Ridge Bioinformatics, we provide solutions for biotech companies and researchers who want the most out of their data. Our expert data scientists can help you unlock new opportunities, steamline existing R&D processes, and conduct rigorous biological analysis.
1) What does global malaria resistance research look like? Can you explain more about what you did on a project like that? Additionally, do you have any thoughts on the irradiation of illnesses like malaria?
On eradication, I think people often look at technology whilst overlooking the human element. Eradicating a disease is a huge task. You need both the ability and the will to do so, which means you need bed nets, antimalarials, and vaccines, but you also need the finances and local capacity to fuel that and the communication to allow it.
2) What tools, languages, and programs do you use on a daily basis to build and grow your startup?
Python is our primarily language, but we also use R, PHP, C++ etc. In a way, it really becomes more about the libraries used once a language is learnt, so specific knowledge of packages like Flask, Scikit, Keras etc is big. It’s also about speed of adaptability, new languages like Go and Julia will tend to emerge and packages will always require fast familiarisation. Being able to jump straight in and get something working is key.
3) Can you expand on how bioinformatics works on a practical level?
A lot of this is convention. You need to be happy with a Unix environment to work with basic tools like bwa, samtools, and kallisto. Other times, it’s about matching tools with a job. Simple web tools are better made with Flask, whilst larger platforms will be better suited to Django. Practically, bioinformatics is a diverse and expanding field.
3b) How could someone train themselves to use bioinformatics or try a bioinformatic project to see if it is something that they would enjoy?
There a loads of great tools and tutorials out there. Things like Rosalind are good for providing challenges, whilst sites like codeacademy can help you interactively learn a new language. I would also recommend MOOCs, from sites like Coursera and FutureLearn. The key thing is to learn the basics semi-formally, then learn everything else through experience.
4) What do you both do on a typical day/week? Basically, If we cracked open your startup, what would we see you all doing?
Unix terminal, coding, visualizing, bug fixing, with meetings of all varieties sprinkled in between. As the business is relatively new, we currently all do a bit of everything. This means anything from securing new clients and partnerships, to completing projects, and developing our platform.
5) To what extent have mentors shaped your startup journey, and how have you developed those relationships?
We have a nice mix of scientific and business oriented individuals on our advisory board, and also strive to bounce concepts off people from diverse educational backgrounds. Going forward we want to build a diverse team and advisory board as we believe this is key to our success.
6) Are there things going on in the science community that keep catching your attention? If so, what?
Recently, there has been a large shift towards the concept of ‘freelance science’ as scientists move into more creative ways of working on different passion projects. You can see this in the rise of biotech entrepreneurship, science blogging, software hackathons, and groups such as the London Biohackspace. It’s this spirit of doing more of what you enjoy, whilst developing a personal skill set that we’re keen to tap into.
7)Where do you see the future of the industry (or specific focus) going?
Everything is going to get bigger and better, with more data and better analyses as we see bioinformatics and data science being more accepted and integrated into traditional wet-lab biotech companies. We are also seeing that the cost of generating data is decreasing year on year, and more data means a greater need for more bioinformatics.
8) If your startup succeeds, what additional areas might you be able to expand into?
We think our fundamental model has broader applications, but want to first root ourselves into the biotech industry. Our core model has potential applications for other scientific fields, but also industries such as intech. However, this is several years away at present.
9) What advice would you give someone starting out?
Be willing to give it your all and take risks. You have got to have a lot of resilience and persistence as you will be faced with a lot of no’s and rejection from people who don’t fully understand or see the potential in your idea. However, if you know that your idea/business addresses a customer’s problem, is better than any existing solution, and that there is a market for it, keep pursuing your goal and building as it will work out.
10) What has been the most rewarding?
Turning what started out as an idea discussed over coffee to a profitable business and knowing that this business is there because of you and your team. Also, working with others who feel passionately about what we are doing and who are ambitious for the future.