meet the trainer – EMBL Events

Meet the trainer: Isidro Cortes Ciriano

We sat down with Isidro Cortes Ciriano to discuss his involvement with the upcoming EMBL-EBI Cancer genomics course, and find out what training means to him.

Cancer genomics | 20 – 24 June 2022 | Hinxton, UK

Hi Isidro! Tell us a bit about yourself for those that don’t know you.

I joined EMBL-EBI in 2019 as a research group leader. My team focuses on the development of computational tools to understand the molecular alterations underpinning cancer, with a focus on the analysis of somatic mutations using sequencing data.

I am also one of the scientific organisers of this year’s EMBL-EBI Cancer genomics training course.

What is your research focus, and how long have you worked in your scientific field?

I obtained my PhD at the Pasteur Institute in 2015 before completing postdoctoral training at Harvard Medical School, under the supervision of Prof. Peter Park, and at the University of Cambridge, under the supervision of Prof. Andreas Bender. My expertise includes biology, genomics and statistical modelling.

Tell us more about the Cancer genomics course you’re involved in. What advice would you give to anyone thinking of applying?

Do it! The course provides an exciting opportunity to learn about the latest approaches for cancer genome analysis, with relevance for both research and clinical applications.

That sounds great! How has training influenced or assisted your own career do you think?

Training at the MSc/PhD level is fundamental to cement basic knowledge in the field. This includes both reading literature and hands-on training to understand the particularities and limitations of the algorithms we use, all of which helps acquire the necessary expertise to drive research projects in a rigorous manner.

Thanks Isidro, we can’t wait to hear you talk at the course this June.

Join Isidro Cortes Ciriano at EMBL-EBI's Cancer genomics training course. — Join Isidro Cortes Ciriano at EMBL-EBI’s Cancer genomics training course.

Applications for Cancer genomics are now open until 11 March 2022.
View the full programme and apply now.

Meet the Trainer – Jonathan Manning

PHOTO: Jonathan Manning

The Introduction to RNA-seq and Functional Interpretation course (21 – 25 February 2022) is now open for applications and we thought we would introduce you to one of the course trainers, Jonathan Manning.

Jonathan is a Bioinformatician in the Gene Expression group. His role is to expand capacity for single-cell RNA-seq analysis, the Expression Atlas resource, in dialogue with the Human Cell Atlas project. Jon gives us his tips for when looking for scientific training and some inside information on what he would be if he wasn’t a Bioinformatician.

What is your research focus and why did you choose to become a scientist?

My answer here is going to be awkward, in that I don’t have a research focus! Much of my career has been as a ‘service’ Bioinformatician working in various bioscience institutes performing custom analysis for a variety of different experiment types in different biological fields. In my current role at EMBL-EBI I build and maintain RNA-seq pipelines we run the same way over a large number of experiments. In both cases, I use the outputs of other people’s research (tools as well as data) to produce the best results I can for the questions at hand.

I actually started out in Biochemistry due to a fascination with the molecular machinery of life. But I discovered early on that the lab was not for me, and I’ve been on the ‘dry’ side of things ever since.

Where do you see this field heading in the future?

In common with many other fields, machine learning and artificial intelligence will play progressively bigger roles in this field in the coming years, with ‘Big Tech’ companies such as Google having ever greater involvement. I’m sure this will be a double-edged sword, and people such as myself will have to run to keep up, but there’s no denying the potential of these techniques and I foresee some exciting results.

How has training influenced your career?

I’d say my early Bioinformatics training (a Masters by Research and PhD after that) was pretty pivotal for me, setting me on a whole new path. After that my training was more incremental, for example, some introductory RNA-seq analysis similar to that offered at EMBL-EBI, followed up with a lot of self-teaching.

What is your number one tip for people looking for scientific training?

Be focused, choose courses that are related to your immediate objectives, and have clear goals about what you want to get out of the training. If you don’t have ways to immediately apply and expand what you’ve learned then the training quickly fades. I often find it more useful to do training only once I’ve tried to do something myself, so that I know which bits are tricky for me and what questions I need to get answers for.

If you weren’t a scientist, what would you be?

I’d really love to study historical linguistics, an interest I’ve picked a bit late in the day. I also learned to dance a bit over the last several years, maybe I’m a professional dancer in another universe where I started earlier!

Interested in this course? Apply by 12 November 2021

For more upcoming events on cancer research take a look at our event listing.

Meet the Trainer – Varsha Kale

PHOTO: Varsha Kale

Meet Varsha Kale, a Bioinformatician in the Finn team: Microbiome Informatics at EMBL-EBI and one of the trainers at the EMBL Course: Metagenomics Bioinformatics (08 – 12 November 2021).

We virtually sat down with Varsha and quizzed her on where she thinks the field of Metagenomics is heading in the future; and some inside information on what you can expect from the course.

What is your research focus and why did you choose to become a scientist?

Using metagenomics to characterise the chicken and salmon gut microbiome and its functions.

I enjoyed learning about bacteria and how they thrived in various environments. This opened a world of different microbes from symbiotic, commensal to pathogenic and highly resistant. It was exciting! When working in a lab, we would receive pre-analysed sequencing data from bioinformaticians. My mentors at the time were supportive to indulge my curiosity as to how the analysis was performed and hence I chose to study bioinformatics. At EMBL-EBI I have the opportunity to learn about new tools and analysis methods frequently.

Where do you see this field heading in the future?

The continued expansion of novel genomes and annotations deposited in public archives will give us more and deeper insight into some elusive environments. Additionally, as statistical modelling becomes more popular, many of the methods we use for annotation are adopting machine learning techniques. The challenges will be the integration of different data types, judging the optimal cutoffs for accurate annotation, and continuing to ensure that all of these new types are easily available through community-adopted public repositories.

How has training influenced your career?

I have been lucky to have opportunities to attend training courses which helped tremendously with understanding the basics of a new subject. Also, a field such as metagenomics is progressing so fast that training gives a great snapshot of the recent updates and methods that others are using for similar research.

What is your number one tip for people looking for scientific training?

Keep up to date with upcoming courses which are interesting to you. Twitter or LinkedIn can be useful for this, or even the webpages of some of your favourite institutions. However, I found that asking colleagues and peers about training courses they have attended is most informative.

If you weren’t a scientist, what would you be?

To be honest, I went home one day from school and startled my parents with the news that bacteria are the new “cool” – so I’m not sure that I would have done something else! I enjoy singing and it might have been fun and challenging to pursue that.

Which methods and new technologies will be addressed in the course?

There is currently a lot of interest in generating metagenome assembled genomes (MAGs) from microbiome data, so we will work through this process including potential tools you might use for the various steps, as well as things to consider in controlling the quality of your data. An introduction to MGnify will also highlight the specialised pipelines used to analyse different types of microbiome data: amplicon, WGS reads, and assemblies.

What are the highlights of the course?

The course will give an overview of metagenomic data analysis including, browsing public data, quality control, and assembly of sequenced metagenomes, tools, and methods to analyse metagenomic data and submission to public archives. There will be a mixture of live and recorded talks, practicals, and Q&A’s with lots of opportunities for discussion. A personal highlight is the chance to learn about the research projects of others attending the course!

Interested in this course? Apply by 03 September.

For more upcoming events on cancer research take a look at our event listing.

Meet the Trainers – Tobias Rausch and Alexey Larionov

On the occasion of World Cancer Day (4 February), we meet two of the trainers of the virtual EMBL Course: Cancer Genomics (17 – 21 May 2021) – Tobias Rausch and Alexey Larionov.

PHOTO: EMBL Photolab

Tobias Rausch (TR) received his PhD in “Computational Biology and Scientific Computing” at the International Max Planck Research School in 2009. He then started to work at the European Molecular Biology Laboratory (EMBL) as a bioinformatician. His primary research interests are population and cancer genomics, structural variant discovery and omics computational methods development. (https://github.com/tobiasrausch).

PHOTO: Alexey Larionov

Initially educated as a clinical oncologist in Russia, Alexey Larionov (AL) switched to experimental oncology upon completion of his PhD. Initially he worked as a postdoctoral researcher in Edinburgh University studying transcriptomics of breast cancer, with a focus on markers and mechanisms of endocrine response and resistance. Working with data-rich methods (qPCR, micro-arrays, NGS) he became interested in data analysis and switched to bioinformatics. Since completing his MSc in Applied Bioinformatics, Alexey has worked as a bioinformatician at Cambridge University, focusing on NGS data analysis and heritable predisposition to cancer. See http://larionov.co.uk for more details.

What is your research focus?

TR: Computational genomics.

AL: Heritable predisposition to cancer

Why did you choose to become a scientist?

TR: When I started at EMBL I saw myself as a software engineer who loves to design, develop and implement algorithms to solve data analysis problems. With the advent of high-throughput sequencing, this engineering background gave me a competitive edge as a data scientist, and that’s how it happened!

AL: It was interesting…

Where do you see this field heading in the future?

TR: Nowadays cancer genomics is a data-driven team science, but it is a long way from obtaining data to obtaining insight. In the age of analytics we all have to wrap our heads around multi-domain data with spatio-temporal resolution, ideally in real-time.

AL: I assume that the question is about translational cancer research in general. I expect that in the near future the field needs better integration of different types of biological data and better collection of relevant clinical data.

How has training influenced your career?

TR: I think training is essential to get you started. Training is like a kind person who takes your hand and guides you through unknown territory. It goes along with mentorship and I was lucky enough to have good training and good mentorship already as a student.

AL: Since my initial clinical and bioinformatics degrees, cancer research has changed so much that I would not be able to even understand current papers if I hadn’t taken regular in-depth training in different aspects of computing and bioinformatics.

How has cancer research changed over the years?

TR: I hope I am still too young to answer that :-). I leave that question for Bert Vogelstein or Robert A. Weinberg.

AL: Cancer research has become much more complex and powerful because of the development of new methods; specifically significant progress in bioinformatics, sequencing and human genomics.

Which methods and new technologies will be addressed in the course?

TR: We try to give an overview of how high-throughput sequencing can be applied in cancer genomics. We cover a range of technologies (short-read and long-read sequencing), data types (RNA-Seq, DNA-Seq and ATAC-Seq) and data modalities (bulk and single-cell sequencing), and last but not least – we take a deep dive into cancer genomics data analysis.

AL: In my sections of the course, I will discuss established methods for the analysis of bulk RNA sequencing, focusing on differential gene expression. Then I will touch on the new methods being developed for the analysis of long-read RNA sequencing.

What learning outcomes should participants expect to take home after the course?

TR: To come back to my previous answer: I hope after the course, cancer genomics won’t be an unknown territory anymore for the participants. I hope we pave the way and then it’s up to the students to make something out of it.

AL: In my section of the course, participants will learn:

1) Bioinformatics algorithms and tools for QC, alignment, and gene expression measurement in bulk short-read RNA-sequencing data

2) Current approaches to analysis of long-read RNA-seq data, comparing the Oxford Nanopore and PacBio sequencing technologies.

Interested in this course? Apply by 26 February.

For more upcoming events on cancer research take a look at our event listing.

Meet the Trainers: Quantitative Proteomics Course

Meet Christina Ludwig (CL), Jeroen Krijgsveld (JK) and Mikhail Savitski (MS) – organisers of the virtual EMBO Practical Course: Quantitative Proteomics: Strategies and Tools to Probe Biology (3 – 7 May 2021). Since it first took place in 2016 it has grown in popularity and application numbers, reaching 164 applications for 24 seats in 2018. Christina, Jeroen and Mikhail share with us how the course has developed over the years and what their vision is for its future.

1. This year marks the 5^th edition of the Quantitative Proteomics course. Back in 2016, why did you decide to organise it?

JK: The main motivation to initiate the course was because proteomics has become a mature technology that is increasingly being used by biologists to identify proteins, their modifications, interactions etc. However, few biologists have direct access to mass spectrometers, so they use them via collaborators or core facilities. They then get the results in a tabular form, often in a large excel sheet, from which they extract biological interpretation of the experiment. Importantly, we felt that the area between handing in a sample for mass spectrometric analysis and receiving the results was largely a black box. So in the course we aimed to demystify this, and explain the principles and strategies to generate information from raw MS data, and to train them in the use of computational tools to achieve this. Also, we aimed to give insight that proteomics can be done in various ways, so that participants may design their experiments such that they best address the question they are looking to answer. Finally, we aimed to equip participants with some terminology that will help them to communicate with their MS-collaborators, and ask the right questions. Because in many cases proteomics remains a team effort!

2. How has the course developed since?

JK: Proteomics is a very broad field with many mass spectrometric approaches, methods for data analysis and biological applications, making it impossible to cover this in a 1-week course. While in all editions of the course we have maintained a core that explains the main principles in proteomics and covers all of the current state-of-the-art quantitative technologies used in proteomics. Additionally, we have included other elements that varied over the years, to highlight emerging topics or specific application areas, e.g. in structural biology or immunology.

3. How do you choose which bioinformatics tools to cover in the course?

JK: There is an increasing number of bioinformatic tools that can analyse the same data using different underlying algorithms. Several of them have matured a lot over the years, making them more robust or have additional functionality. It is not always easy for anyone to know, when looking for an ‘analysis pipeline’, which tool can be best used. It can actually be a bit confusing that the same data can produce different results depending on the tool that is used, while at the same time none will be wrong. So instead of telling which tool is the best, we explain some of the underlying assumptions and the influence one has by choosing certain settings. I think for a researcher it is more important to justify how the data were processed, instead of saying that they used a certain software tool.

4. What could the techniques in this course be used for in the bigger picture?

CL: Proteomics technologies have reached a level of comprehensiveness, throughput and quantitative quality that was inconceivable just a few years back. However, applying proteomics to biological projects still requires lots of knowledge about experimental design, optimal sample preparation, most suitable mass spectrometric technologies and statistical interpretation. If we manage to bring both worlds together and teach biologists about the power, as well as the caveats, of proteomics, I think this will really impact life science in many aspects and truly transform the way how scientific projects are carried out for many scientists all over the world.

JK: I agree. Demonstrating the versatility, and thereby the potential and broad utility of proteomics in different contexts is sometimes an eye-opener for course participants. Actually, it is interesting and useful that participants come from all corners of biology, from paleobiology to clinical biomarker discovery. Having those together in a virtual room for a week and interact, with proteomics as the common interest, is fascinating to see as an organiser. And we explicitly facilitate such interactions in discussion groups – it is an important goal of the course.

5. How do you see this course growing in the future?

CL: I think one special feature of this course, compared to other proteomics courses, is that its rather familial in character due to the small number of 24 participants, and that they come from purposefully different countries and research institutes. This rather small group size is optimal in terms of group dynamics and allows lots of personal exchange between participants and speakers, as well as an optimal support during the practical sessions. Therefore, I hope also in the future the small and familiar atmosphere of this course will remain.

Due to the COVID-19 pandemic, this edition of the course will be 100% virtual. While we look forward to switching back a physical course format, we can definitely envision future courses with virtual components that entail those teaching-elements that work well in the virtual world, and are thereby easily accessible to a lot of people without traveling.

JK: What I also hope, and what we’ll try to achieve, is to remain up-to-date and include novel technologies that are emerging. After 20 years of steep development in mass spectrometry, one would expect that this levels off at some point, but this is not the case at all – it is actually difficult to keep up with what is happening, and with what is possible today that you would not dare to think about yesterday. Therefore, a remaining goal for us is to invite speakers and trainers who work at the forefront of technology, but who can also bridge this to important biological applications. This is what excites us as organisers, and we hope that this will help to make this one of the courses to go to for younger generations of scientists, and get infected too.

6. What motivates you most about your work?

CL: What I really love about heading a proteomics core facility is the huge variety of cool scientific projects you get exposed to, as well as the fact that you work closely with lots of very different scientists coming from completely different scientific disciplines. Every project and every collaboration partner challenges you in terms of diving into a new research area, providing an optimal proteomic workflow and also teaching and educating your collaboration partners in understanding their proteomic data.

MS: The fact that you have the constant possibility to come up and implement creative ideas is incredibly rewarding. Also the fact in research you are constantly generating results that are the first of their kind. There is always an experiment done that has not been done by anyone before and you are the first to see the results. I also love the academic environment the freedom and craziness of it all.

7. Why did you end up in the field of Proteins and Proteomics?

CL: Already during my Chemistry studies all the “biochemistry” lectures and practicals that focused on proteins and life sciences were by far the most interesting subjects for me. During my PhD, which I did in the field of protein engineering at the TU Dortmund, I studied a specific class of proteins, so called inteins, but I hardly applied any mass spectrometry during that time. However, for one specific experiment I used for the first time MALDI-MS to identify the reaction products of a set of purified inteins. My MALDI measurements showed the occurrences of an unexplainable loss of 18 m/z for one of my inteins. First I thought I did a mistake and was very frustrated. But when I repeated and further investigated my samples using also ESI tandem mass spectrometry I could proof the existence of a very interesting cyclic protein-intermediate, which actually helped me explaining the underlying protein splicing mechanism. This turned out being the most interesting result of my whole PhD.

MS: I originally was very focused on pure mathematics. By chance I had an encounter with Roman Zubarev who was a new professor at Uppsala University at the time. His drive, energy and passion for science convinced me to switch fields from mathematics to mass spectrometry and proteomics, which I never regretted.

8. What could you not do without in your life?

CL: Well, as a mother of two beautiful kids the very first thing I could not do without in my life is of course my family :)! And together with my family we love being outdoors, ideally in the Alps, either on (mountain)bikes, rock climbing or hiking. Living without mountains and outdoor activities would be very hard.

MS: First and foremost, my family! Second is physical activity. I love science and I love working a lot, but it takes its toll physically and mentally. My perfect way of recovering and getting the energy back is ideally by rock climbing, running and being out in nature in general.

9. If you would get the chance to meet a famous person – no matter if this person is still alive or not – who would that be?

CL: As a hobby climber I would really like to once meet Alex Honold, who is a world famous free-solo climber who climbed many of the most difficult and exposed climbs in Yosemite National Park without rope. Alex seems in interviews and videos like a really nice and funny guy, but I believe his brain must function very differently than mine when it comes to fear of height, so I would love chat with him about that ;).

MS: I was always interested in mathematics as well as computer science. It would have been fascinating to meet Alan Turing and discuss his vision of how things would develop based on what he knew back then. Incidentally, he was also a really excellent long distance runner with sub 3 hours’ marathon times. It would have been exciting to have a discussion over a run on the countryside :).

10. Which was the best decision in your career so far?

CL: I think the best decision for my career was to perform my Postdoc in the group of Professor Ruedi Abersold at the ETH Zürich, because this has really been the door opener for my career so far. When I finished my PhD it was actually not easy for me to decide for a postdoc in the field of mass spectrometry, because I hardly had any MS experience (I only performed this one MS experiment that I already described above ;)). And starting in a proteomics expert lab as a postdoc who had never really done proteomics before was definitely not easy in the beginning. But I did learn a lot of new things fast and ultimately this allowed me to bring together the two different expertises from my PhD and my Postdoc, which I do believe is a big advantage for any scientific career.

MS: Professionally, I think doing PhD in mass spectrometry was probably the best decision I have made so far. That early in your career, one still knows very little of the world and some luck is definitely required.

Interested in this course? Apply by 8 March!