Professor Mikael Boden
Professor

Mikael Boden

Email: 
Phone: 
+61 7 336 51307

Background

Mikael Bodén has a PhD in Computer Science and statistical machine learning from the University of Exeter (UK) but has spent the last decade and a half in biological research environments, including the Institute for Molecular Bioscience/ARC Centre of Excellence in Bioinformatics and the School of Chemistry and Molecular Biosciences, where he is currently located. He is the director of UQ’s postgraduate program in bioinformatics. Mikael Bodén has supervised 7 postdocs from funding he received from both ARC and NHMRC; he has been the primary advisor for 11 PhD and 3 MPhil graduates; he is currently supervising another 6 PhD students in bioinformatics and computational biology. Mikael Bodén collaborates with researchers in neuroscience, developmental biology, protein engineering and bioeconomy to mention but a few, and contributes expertise in the processing, analysis and integration of biological data; this is exemplified by recent publications in Science, Nature Catalysis, Nature Communications, Cell Systems, Nucleic Acids Research and Bioinformatics.

Availability

Professor Mikael Boden is:
Available for supervision
Media expert

Fields of research

Bioinformatics and computational biology Biological Sciences Genetics Genomics Information and Computing Sciences Modelling and simulation Systems biology

Qualifications

  • Bachelor of Science, Skövde University College
  • Masters (Coursework) of Science, Skövde University College
  • Doctor of Philosophy, University of Exeter

Research interests

  • Bioinformatics

    Thanks to major advances in biotechnology and instrumentation, biology is becoming an information centred science. The field of bioinformatics draws on computer science, math and statistics to enable discoveries in biological data sets. Our research aims to develop, investigate and apply bioinformatics methodologies to understand and resolve a range of open problems in genomics, molecular and systems biology. Recent applications involve protein sorting, nuclear protein organisation, mechanisms of transcriptional regulation, sequence and structure determinants of protein function and modification, and protein engineering. Biological data are now available at scales that challenges our ability to process and analyse them. On the flip side, greater scale gives statistical power to distinguish biologically meaningful signals from mere noise or artefacts, i.e. to identify "drivers" and "determinants" of function and structure. Sometimes the number of features (that describe each observation) is so great that we must use (biological) expertise to constrain the search for signals. Broadly put, our research aims to 1. effectively manage the complexity of operations involved in analysing millions of sequence reads, thousands of genomes, and proteomes of thousands of dynamically regulated molecules, etc 2. enable the seamless aggregation (or integration) of uncertain and incomplete data, typical of the next wave of biotechnology, across genomics, proteomics, structural biology, etc, and of using biological expertise 3. empower the interpretation of "whole system" data, aimed at understanding of basis of disease and other scientifically relevant phenotypes, using statistics and machine learning

Search Professor Mikael Boden’s works on UQ eSpace

129 works between 1993 and 2024
All (129) Journal Article (93) Book Chapter (4) Conference Publication (31) Edited Outputs (1)

121 - 129 of 129 works

2000

Journal Article

Semantic systematicity and context in connectionist networks

Boden, Mikael and Niklasson, Lars (2000). Semantic systematicity and context in connectionist networks. Connection Science, 12 (2), 111-142. doi: 10.1080/09540090050129754

Semantic systematicity and context in connectionist networks

1999

Conference Publication

Content, context and connectionist networks

Niklasson, L. and Boden, M. B. (1999). Content, context and connectionist networks. 21st Annual Meeting of the Cognitive Science Society, Vancouver, August 1999. New York, NY, United States: Lawrence Erlbaum.

Content, context and connectionist networks

1999

Conference Publication

On the ability of recurrent nets to learn deeply embedded structures

Boden, M. B., Wiles, J. H., Tonkes, B. and Blair, A. D. (1999). On the ability of recurrent nets to learn deeply embedded structures. IJCAI'99, Stockholm, 31 July - 6 August 1999. Stockholm: IJCAII.

On the ability of recurrent nets to learn deeply embedded structures

1999

Conference Publication

An experimental comparison of weight evolution in neural control architectures for a 'Garbage-Collecting' Khepera robot

Ziemke, T., Carlsson, J. and Boden, M. (1999). An experimental comparison of weight evolution in neural control architectures for a 'Garbage-Collecting' Khepera robot. 1st International Khepera Workshop, Paderborn, Germany, 10-11 December 1999. Paderborn, Germany: HNI-Verlagsschrittenreihe.

An experimental comparison of weight evolution in neural control architectures for a 'Garbage-Collecting' Khepera robot

1999

Conference Publication

Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units

Boden, M. B., Wiles, J. H., Tonkes, B. and Blair, A. D. (1999). Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units. ICANN'99, Edinburgh, Scotland, 7-10 September, 1999. London, United Kingdom: IEE. doi: 10.1049/cp:19991135

Learning to predict a context-free language: Analysis of dynamics in recurrent hidden units

1996

Conference Publication

A connectionist variation on inheritance

Bodén, Mikael (1996). A connectionist variation on inheritance. 1996 International Conference on Artificial Neural Networks, ICANN 1996, , , July 16, 1996-July 19, 1996. Springer Verlag. doi: 10.1007/3-540-61510-5_62

A connectionist variation on inheritance

1995

Conference Publication

Features of distributed representations for tree-structures: A study of RAAM

Boden, M and Niklasson, L (1995). Features of distributed representations for tree-structures: A study of RAAM. Swedish Conference on Connectionism, Skovde Sweden, Mar 02-03, 1995. MAHWAH: LAWRENCE ERLBAUM ASSOC PUBL.

Features of distributed representations for tree-structures: A study of RAAM

1993

Journal Article

Connectionism

Boden, MB and Niklasson, LF (1993). Connectionism. Artificial Intelligence Review, 7 (5), 259-260. doi: 10.1007/BF00849053

Connectionism

1993

Conference Publication

A Representational Architecture for Nonmonotonic Inheritance Structures

Bodén, Mikael and Narayanan, Ajit (1993). A Representational Architecture for Nonmonotonic Inheritance Structures. ICANN 1993: International Conference on Artificial Neural Networks, Amsterdam, The Netherlands, 13-16 September, 1993. London, United Kingdom: Springer London. doi: 10.1007/978-1-4471-2063-6_79

A Representational Architecture for Nonmonotonic Inheritance Structures

Current funding

  • 2023 - 2026
    What drives the Anterior Expansion of the Central Nervous System?
    ARC Discovery Projects
    Open grant
  • 2023 - 2024
    What is the common factor driving brain overgrowth in ASD? Investigating the relationship between epigenetic marks neural stem cell proliferation.
    Simons Foundation Autism Research Initiative - Pilot Award
    Open grant
  • 2022 - 2026
    TRIAGE: A disease agnostic computational and modelling platform to accelerate variant classification
    NHMRC MRFF Genomics Health Futures Mission
    Open grant
  • 2022 - 2024
    Dual-function ribonucleases: unexpected agents of antibiotic resistance
    NHMRC IDEAS Grants
    Open grant

Past funding

  • 2021 - 2024
    EnzOnomy - an enzyme-based production pipeline for the bioeconomy
    ARC Discovery Projects
    Open grant
  • 2016 - 2019
    Reconstructing proteins to explain and engineer biological diversity
    ARC Discovery Projects
    Open grant
  • 2012 - 2015
    Tracing nature's template: Using statistical machine learning to evolve biocatalysts
    ARC Discovery Projects
    Open grant
  • 2011
    A systems biology approach to elucidate common principles and mechanisms underlying triplet repeat expansion associated genetic defects
    NHMRC Project Grant
    Open grant
  • 2005
    Mining Long-range Dependencies and Interactions in Amino Acid Sequences
    UQ Early Career Researcher
    Open grant
  • 2003 - 2005
    Recurrent neural networks for biological sequence analysis
    UQ New Staff Research Start-Up Fund
    Open grant

Availability

Professor Mikael Boden is:
Available for supervision

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Supervision history

Current supervision

  • Doctor Philosophy

    Bioinformatics of epigenetics at multiple scales: from evolution of epigenetic factors to tracing their marks in organellar development

    Principal Advisor

    Other advisors: Professor Stefan Thor

  • Doctor Philosophy

    Do cell types exist in a continuum? Single-cell bioinformatics across species, over time and space

    Principal Advisor

    Other advisors: Professor Stefan Thor

  • Doctor Philosophy

    Finding meaningful variation in biological data by deep learning

    Principal Advisor

    Other advisors: Dr Gabriel Foley

  • Doctor Philosophy

    Merger of natural and engineered biological sequence space

    Principal Advisor

    Other advisors: Dr Michael Forbes

  • Doctor Philosophy

    Dual-function ribonucleases: unexpected agents of antibiotic resistance

    Principal Advisor

    Other advisors: Professor Phil Hugenholtz, Dr Gabriel Foley

  • Doctor Philosophy

    Using Statistical Models to Integrate Epigenetic Information by Distinguishing Sources of Variability

    Principal Advisor

    Other advisors: Professor Michael Piper, Dr Gabriel Foley

  • Doctor Philosophy

    How SETD2 shapes cortical development

    Associate Advisor

    Other advisors: Professor Stefan Thor, Professor Michael Piper

  • Doctor Philosophy

    Changing the prokaryotic classification status quo with a global genome-based taxonomy

    Associate Advisor

    Other advisors: Professor Phil Hugenholtz

  • Doctor Philosophy

    Decoding the genetic pathways governing cell diversity in the mammalian hypothalamus

    Associate Advisor

    Other advisors: Professor Michael Piper, Professor Stefan Thor

Completed supervision

Enquiries

Contact Professor Mikael Boden directly for media enquiries about:

  • Artificial Intelligence (AI)
  • Bioinformatics
  • Biology and computers
  • Computational biology
  • Computer learning
  • DNA sequencing
  • Machine learning
  • Systems biology

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