Simon Hubbard, BSc, PhD


Personal profile

Research interests

I am a Professor in the Faculty of Biology, Medicine and Health at the University of Manchester. My scientific career has taken me from a PhD in Biochemistry at UCL, London, via the European Molecular Biology Laboratory, back to Manchester in the UK where I undertook a Wellcome Trust fellowship, before gaining a Lectureship in 1998. My research covers themes in computational and systems biology and bioinformatics. My research applies computational approaches to the study of biological systems and molecules, and my particular areas of interests are detailed below, broadly in the areas of protein and genome bioinformatics including quantitative proteomics, regulation of gene expression (and particularly translation from mRNA to protein), and general bioinformatics.

Applied Quantitative Mass Spectrometry-based Proteomics

Proteomics seeks to characterise the proteins produced in a cell or tissue, exploiting sequenced genomes to identify proteins, usually via mass spectrometry. Bioinformatics plays an important role in this process by bridging the gap between the experimental data (mass spectra) and the databases of protein sequences, to identify (and ideally quantify) proteins via their constituent peptides. We have developed algorithms for this purpose, to improve protein/peptide identification and associated statistics. Alongside this work, we are closely involved in the efforts to develop data standards and databases to store and mine all the data emanating from proteomics experiments. We are interested in quantifying the proteomes of whole organisms, including yeast, to understand how protein levels vary between different genes - some mRNA:protein ratios are < 10, others are > 250,000. A second major project (a sLoLa funded by the BBSRC) is seeking to quantify the developmental proteome of the fruit fly, Drosophila, with colleagues in Cambridge and UCL. All of the projects require bionformatic tools both to process the data and derive accurate estimates, as well as tools to analyse the data and look for patterns and trends and improve our understanding of these fundamental processes.

We are also investigating how proteomics can help annotate genome sequences (see below) and how SWATH-MS informatics tools can be used to discover novel biomarkers in collaboration with the Whetton lab in the Stoller Centre.

Genome and Transcriptome Sequence Analysis, including Proteogenomics

Our group also study DNA and protein sequences to understand biological phenomena. We played the leading role analysing EST and cDNA sequences as part of the international effort to sequence the chicken genome, providing web-based resources for chicken ESTs, cDNAs, SNPs and a proteome database. In addition to the chicken work, we are also analysing transcriptome sequences in yeast in order to understand how these are translationally regulated, looking at how RNA binding proteins involved in regulating these process. This is part of a collaboration with the Ashe, Pavitt and Grant labs funded by the BBSRC. Finally, we also attempt to exploit transcriptome data (such as ESTs or from RNA-seq projects) to predict novel proteome databases from which we can identify novel genes and gene structure via mass spectrometry data - this field is known as proteogenomics, and can add great value to the annotation of genome sequences by finding information that the original annotators had missed.

Current funding: BBSRC


Our group is interested in using computers to understand biological phenomena, via data analysis, modelling and prediction. Our main focus at present is on the area of quantitative proteomics: how can we measure the levels of all the individual proteins in cells and tissues, and understand how these levels change in different conditions, as well as under stress. We are working on methods to do this in collaboration with mass spectrometrists and protein chemists, developing software for experimental design and downstream analysis of results, using yeast and the fruit fly as model systems. In parallel, we are analysing experimental RNA sequencing data in yeast to understand how cells regulate the translation of mRNA in to proteins, a fundamental process of molecular biology which is now know to play a significant role in the regulation of gene expression, particularly under stress conditions.


Post-genome biology: how are modern techniques in biology changing the experiments we can do and the questions we address? I teach in Undergraduate and MSc courses looking at how transcriptomics and proteomics can study molecules in the cell on a genome-wide basis.

Biocomputing: I teach on MSc courses providing background on the basics of programming for bioscientists, as well as the theory and algorithms underpinning areas of computational biology


Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Research Beacons, Institutes and Platforms

  • Biotechnology
  • Digital Futures
  • Institute for Data Science and AI


  • proteomics
  • bioinformatics
  • systems biology
  • yeast
  • Drosophila
  • gene expression
  • translational control
  • RNA binding proteins


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