Most of the stats we are exposed to in our formative years as statisticians are viewed through a frequentist lens. Bayesian methods are often viewed with scepticism, perhaps due in part to a lack of understanding over how to specify our prior distribution and perhaps due to uncertainty as to what we should do with the posterior once we’ve got it.
Continue readingde novo Small Molecule Design using Deep Learning
This is an interesting paper by Zhavoronkov, et al. that recently got published in Nature Biotechnology as a brief communication: https://www.nature.com/articles/s41587-019-0224-x. The paper describes a new deep generative model called generative tensorial reinforcement learning (GENTRL), which enables optimization for synthetic feasibility, novelty, and biological activity. In this work, authors have deigned, synthesized, and experimentally validated molecules targeting discoidin domain receptor 1 (DDR1) in less than two months. The code for GENTRL is available here: https://github.com/insilicomedicine/gentrl.
Reference: Zhavoronkov, A. et al. Deep learning enables rapid identification of potent DDR1 kinase inhibitors. Nature Biotechnology 2019, 37, 1038-1040.
COSTNET19 Conference
Last month, I attended the COSTNET19 Conference in Bilbao (Spain). This conference is organised by COSTNET, a COST Action which aims to foster international European collaboration on the emerging field of statistics of network data science. COSTNET facilitates interaction and collaboration between diverse groups of statistical network modellers, establishing a large and vibrant interconnected and inclusive community of network scientists.
Continue readingYou’re getting on my biscuits
Jaffa cakes are God’s own snacks and I will brook no opposition. I don’t mind if they’re McVitie’s brand Jaffa cakes, or Pim’s, the suspicious European variety. Even Sainsbury’s Basics Jaffa cakes float my balloon. Take a soft sponge base, slap some jam and chocolate on that puppy, and you’re golden.
But if you describe your love of these glorious creations, the conversation takes a familiar turn. Are they cakes or are they biscuits? it goes. HMRC tried to classify them as cakes – or was it biscuits? Something like that. It had to do with VAT…
Continue readingCommon denominators between a PhD and an Oxford ball
One of the things I love about Oxford is the way it pushes you to become a well-rounded person. It does so by means of a wealth of talks and lectures, and also through the college system that encourages meeting people from different disciplines, but above all through the strong culture of student projects. This place will encourage you, perhaps even push you, to take part in fantastic projects that will make the already very demanding workload even worse… but also teach you incredible skills and get you to work with wonderful, inspiring people.
Continue readingWhat are Hotspots in Structural Biology?
“Hotspot” is one of those extremely versatile words, similar to “model” and “buffer”, which can mean a variety of things depending on context. According to Merriam-Webster, a hotspot is “a place of more than usual interest, activity, or popularity”. This is the most general definition of the concept I could find in a quick search, and the one I find closest in spirit to the way hotspots are perceived in a structural biology context. What this blog post is definitely not about are hotspots as “areas of political, military, or civil unrest” (my experience with them has so far been mostly peaceful), or anything to do with geology, WiFi connections, or forest fires.
However, even within the context of structural biology and structure-based drug design, the word “hotspot” has multiple meanings. In this blog post, I will try to summarise the main ones I have come across, the (sometimes subtle) differences between them, and provide a few useful papers to serve as an entry point for interested readers. Continue reading
Invisible Women – Exposing Data Bias in a World Designed by Men
If you are looking for an excellent, data-focussed present to buy for yourself and everyone you love, check out Invisible Women – Exposing Data Bias in a World Designed by Men by Caroline Criado Perez. Having lent my copy to most members of the SABS DPhil program already, I will quote stats from this book to anyone who will listen.
GitHub Link to Text Mining Tool
I have created a GitHub page to share some of the codes that I used to conduct text mining to extract HBV-related genetic information from PubMed Central. This code is easily adaptable to search through sentences that satisfy your keyword search, so please take a look if you are interested: https://github.com/angoto/HBV_Code.
Note: GitHub page is currently unavailable online, but will be accessible in due course.
SAbBox – the easy way to obtain our antibody tools
A significant part of the work we do here in OPIG revolves around antibodies, the proteins of the immune system that bind to and help remove any foreign entities that find their way into the body. Since antibodies can be developed that target basically anything, they have become extremely useful as therapeutics. In our research, we develop computational tools that can be incorporated into various points along the antibody discovery pipeline. These tools include our database of antibody structures, SAbDab, and a series of predictive tools (e.g. structural modelling algorithms like ABodyBuilder) which are known collectively as SAbPred.
Continue readingThings I’ve Learned from Hosting Speaker Events
For the past couple of years I’ve been involved in running the Oxford University Scientific Society. We host weekly talks in Oxford during the Undergraduate Term, inviting speakers from all scientific disciplines to come and discuss their field with our members. Here are four important lessons I’ve learned from being involved!