Working at the intersection of technology and biology, Dr Yuxuan Lan is bringing her wealth of experience in machine learning to the analysis of complex genomes - developing real time analysis of long reads from the Oxford Nanopore MinION.
Yuxuan moved to Norwich from China to study at the University of East Anglia after finishing her undergraduate degree in electronics.
It was around this time that computing was really coming to the fore - not just in how we communicate, but in how we answer a swathe of scientific questions.
Thus, Yuxuan, now working in the Leggett Group at EI, made the switch to computing for her MSc and never looked back.
I am working on a BBSRC funded project to create a general-purpose user friendly tool for real-time analysis of nanopore metagenomic data. Nanopore technology can generate long read sequences and allows real-time access during sequencing. Current software tools for real-time analysis are either limited in functionality or are not open-source or free.
The Leggett group is working to fill this gap. The goal is to make an open-source tool that has a plug-in interface for third party tools, is easy for visualisation, can be run on both HPC and low power computing equipment such as a laptop or computer stick to facilitate in-field and point of care real-time analysis, and so on.
I studied electronics and telecommunications for my undergrad degree. I did a dissertation on designing an office information system which I really enjoyed and decided to learn more about computing.
Before coming to bioinformatics, I was working on computer lip-reading, i.e., automatically recognising speech with only visual input. Imagine trying to buy a train ticket from a kiosk. Instead of having to go through many steps on the screen, wouldn’t it be nice to just tell the computer through a microphone where you want to go?
However, the station may be noisy and this could make an audio speech recognition system ineffective.
Equipped with also a webcam, a computer can understand you better by reading your lips when the surroundings are very noisy, or by both listening to and seeing what you say when it is quieter.
Before coming to bioinformatics, I was working on computer lip-reading - automatically recognising speech with only visual input.
There are many advances - and a significant one is the deep learning. I started my PhD before deep learning started to develop.
At the time, learning algorithms were important but a lot of focus was on designing and selecting features for the algorithm. Now the feature selection can be done by the deep learning.
There is no clear winner. Only expert humans can lip-read, but very good lip-readers can outperform computers. We found that many lip-readers heavily rely on the language model, i.e., context, in order to lip-read. This makes them perform well on a familiar topic but struggle on an alien one.
Computers on the other hand don’t have such concerns - they can train on many topics. Their performance falls between the best and the worst expert lip-readers, based on a paper we published. I believe more progress has been made in the last few years, with the continuous development in machine learning, especially in the area of deep learning.
Computers on the other hand don’t have such concerns - they can train on many topics. Their performance falls between the best and the worst expert lip-readers...
It is a completely new field to me. It took me a few months to start to follow seminars and talks. It is also a fast moving field with people pushing the frontier of science all the time.
I feel it challenging but also enjoyable to be near the forefront of science and discovery.
Ha, it has never been easy. My husband is very supportive and understanding, and more than happy to share the burden of childcare.
It helps that he and I both work at the Earlham Institute where, when it is possible, staff are offered the convenience of flexible working, and it helps us to work around the childcare, for example, taking my child to after school activity classes, or attending a sick child at home.
I’ve done two tea tasting sessions so far. The first time we tried unsmoked LapSang Souchong, and the second time Dian Hong.
Both red teas were well received by the tasters, so I think red tea is the Brits’ favourite, as we all know.
Postdoctoral Scientist Nasmille Larke-Mejía is researching to help improve agricultural practices and increase crop yield as well as impacting the socioeconomic landscape in Colombia, as part of our GROW initiative funded by GCRF-UKRI.
Exploring the basics of bioinformatics at the Earlham Institute - the rewards and the lessons learned.
Dr Laura-Jayne Gardiner realised how essential a bioinformatics skill set was to keep up with advanced genomics - placing her in great stead to becoming an independent researcher.
For many in the bioinformatics world, learning to code is a leap into the unknown. What’s it like doing a bioinformatics PhD?
Arguably, the question here should be, why is Ada Lovelace not more famous?
To celebrate Ada Lovelace Day, we asked staff on Norwich Research Park to tell us of their inspirational role models in STEM, and how they inspired them to pursue a science career.
In our third installment, Pilar Corredor-Moreno, a PhD student in the Saunder’s Group studying wheat yellow rust at EI, shares her fascinating and honest opinions on computing.
Ada Lovelace Day is an international celebration of the achievements of women in science and technology but behind this are the remarkable achievements of the very first computer programmer.
We interview Vanessa Bueno of the Saunders Group, who is a predoctoral student working on wheat yellow rust.
Katie Barr tells us what she thinks may lie in store for those starting out in the world of coding
