-- The London Proteomics Discussion Group --
Proteomics seminar series for the South East

10th July 2020
Proteomics seminar series for the South East
Methods Challenge
---Registration is free---

About the LPDG

We are a free, local proteomics seminar series in the South East,
with a focus towards networking, discussion and supporting early career researchers.

The LPDG...

was founded to bring together the large community of proteomics scientists all working in and around London. We aim to provide a space for discussion, with a focus on methods and early career researchers (two fundamental building blocks of good research!), on all topics related to proteomics. The meetings comprise of research talks framed by a proteomics methods challenge, lunch, refreshments and pizza - they are free to attend thanks to sponsorship.

Meeting Dates:

Next Meeting


These seminars would not be possible without our amazing sponsors.
If you are interested in sponsoring an LPDG seminar,
please get in touch at sponsor@londonproteomics.co.uk

Webinar Programme

Proteomics: The Role of Machine Learning

for 10th July 2020 14:00 BST
Last updated 26th June 2020

How the (data) rich get richer: machine learning as a key driver of MS informatics

Computational proteomics has evolved extensively over the past decade, introducing the first widely successful machine learning approach with the Percolator algorithm for post-processing of identification data, and slowly expanding the capabilities of predictive algorithms for analyte behaviour during liquid chromatography separation and fragmentation. Despite clear advances in these areas, however, the adoption of such predictions in identifications pipelines was very slow to non-existent. This was primarily due to the already quite capable traditional identification algorithms, especially when complemented with Percolator post-processing. The advent of data independent acquisition (DIA) helped to renew interest in these approaches, however, as this approach’s reliance on experimentally-derived spectrum and chromatogram libraries was inherently hampered by the limitations in the data dependent acquisition (DDA) methods used to acquire these libraries. By creating purely predicted libraries, this limitation of having to rely solely on previously observed and identified signals could be overcome. Meanwhile, renewed interest was also sparked in DDA proteomics, as the field had started to diversify into more complex analyses such as metaproteomics, proteogenomics, immunopeptidomics, and open modification searches, all of which revealed inherent limitations in existing, traditional search engines. As it turns out, machine learning based predictions have shown to be highly effective at solving the issues encountered in DIA and complex DDA proteomics approaches, and the production of highly performant algorithms has soared as a consequence. Interestingly, the availability of vast amounts of public data have also enabled a breakthrough in the types of machine learning algorithms that can now be employed on proteomics data, which has seen a surge in the application of complex neural networks (so-called deep learning approaches) in the field. When provided with enough data, these deep learning algorithms deliver extremely good predictions, which will in turn fuel a more sensitive and more robust interpretation of already acquired data. I will here present our latest, cutting-edge developments in machine learning based algorithms for computational proteomics, as well as our applications of these algorithms to the complete re-analysis of all publicly available human proteomics data, to DIA data interpretation, and to COVID-19 assay optimisation.

Prof Lennart Martens
Prof Lennart Martens
Prof Lennart Martens VIB-UGent Center for Medical Biotechnology, VIB and
Department of Biomolecular Medicine, Ghent University

Lennart Martens is Full Professor of Systems Biology at Ghent University, Group Leader of the Computational Omics and Systems Biology (CompOmics) group at VIB, and Associate Director of the VIB-UGent Center for Medical Biotechnology, all in Ghent, Belgium. He also holds a Visiting Group Leader position at EMBL-EBI in Cambridge, UK. He has been working in proteomics bioinformatics since his Master’s degree, which focused on the computational interpretation of peptide mass spectra, and the sequence-dependent fragmentation of peptides. He then worked as a software developer and framework architect for a software company for a few years, before returning to Ghent University to pursue a Ph.D. in proteomics and proteomics informatics. During this time, he worked on the development of high-throughput peptide centric proteomics techniques and on bioinformatics tools to support these new approaches. In 2003 he started the PRIDE proteomics database at EMBL-EBI as a Marie Curie fellow of the European Commission. After obtaining his Ph.D., he rejoined EMBL-EBI to coordinate the newly created PRIDE group for the next three years, firmly establishing the system as the world’s foremost public proteomics data repository. He then moved back to Ghent University to take up his current position, in which he focuses on novel machine learning algorithms for mass spectrometry data analysis, and their application to the large-scale reprocessing of public proteomics data. Prof. Martens has been elected to the Young Academy of the Royal Belgian Academy of Sciences in 2013, to the Human Proteome Organisation (HUPO) Council in 2016, has been elected Vice-President of the European Proteomics Association in 2017, and was admitted as Fellow of the Royal Society for Chemistry in 2018. He also served on the HUPO Executive Board from 2017 to 2019. Dr. Martens received the 2014 Prometheus Award for Research Excellence from Ghent University, and the 2015 ‘Juan Pablo Albar’ Proteomics Pioneer Award from the European Proteomics Association. An author on more than 240 peer-reviewed papers, he has also co-written two popular Wiley textbooks on computational mass spectrometry.




Here is a list of answers to frequently asked questions for speakers, delegates and sponsors

If you still have unanswered questions after reading this page, wish to present a talk, suggest a venue or sponsor a meeting, please contact us.

Organising Committee

The organising committee is made up of early and "not-so-early" career scientists
from academia and industry.
If you are interested in joining the committee, please get in touch.

Dr Harvey Johnston
Dr Harvey Johnston Chairperson, Founder

After my PhD in blood plasma cancer proteomics I moved to the Cancer Proteomics Group at UCL. I founded the LPDG as a focus group for the SE. I am currently at the Babraham Institute investigating protein degradation pathways using proteomics.

Dr Harry Whitwell
Dr Harry Whitwell Communications Officer

I am a post doc at ICL, developing mass spectrometry and data analysis methodology for the study of protein PTMs, in particular methylation. My research is multidisciplinary, using chemistry, bioinformatics and biology. For more info, click here.

Dr Lukas Krasny
Dr Lukas Krasny Secretary

I am a post-doc at the ICR in Paul Huang’s group. My research interest is in extracellular matrix remodelling during cancer progression. From an analytical point of view, I am interested in protein quantification by DIA mass spectrometry.

Dr Roberto Buccafusca
Dr Roberto Buccafusca Treasurer

I manage an MS lab at QMUL. I graduated from Drexel University (USA) in Biomedical Science, completing my PhD work at Harvard University. After a long stint in the private sector, I re-joined academia here in the UK researching lipidomics and proteomics.

Danai Kati
Danai Kati
Danai Kati Committee Member

Danai studied biology and biomedical sciences in Greece. She has worked in numerous labs in England, Singapore, the Netherlands and Greece. Now she is focusing on her PhD at UCL in Primary Biliary Cholangitis analyzing human samples using Mass spectrometry.

Suniya Khatun
Suniya Khatun Committee member

I am a PhD student at UCL on the CellX project in the Thalassinos Lab studying competition in cellular populations using mass spectrometry-based proteomics.

Dr Daniel Conole
Dr Daniel Conole Committee member

Daniel is a post-doc in the lab of Prof. Ed Tate at Imperial College London. His research interests lie in the use of chemical proteomics for better understanding of drug targets, protein function, and post-translational modification dynamics.

Tom Ruane
Tom Ruane Committee member

Tom works for SCIEX in the London region helping customers with MS and 'OMICS applications. He gained an interest in MS from working with Prof Roy Goodacre, Manchester Institute of Biotech. applying -omics and chemometric approaches for rapid food authenticity determination.

Emily Vitterso
Emily Vitterso Committee member

I am a PhD student in the Institute for Women's Health, UCL in the lab of Dr John Timms working on cancer proteomics.

Joanna Kirkpatrick
Dr Joanna Kirkpatrick
Dr Joanna Kirkpatrick Committee member

Joanna Kirkpatrick
Crick Insitute

London and the South East
United Kindgom

Please email with any questions.
Particularly welcome are venue suggestions,
speaker suggestions or if you are thinking of sponsoring a meeting.

This seminar series is run by volunteers from academia and industry. We will try to reply to your email as quickly as possible, but please allow at least 5 days.