Lukas Folkman
Research Fellow
machine learning | data science | environmental modelling | computational biology

Coastal and Marine Research Centre &
Institute for Integrated and Intelligent Systems
Griffith University, Australia

Curriculum vitae Contact Research & profiles Tools & downloads Publications

About me

I am a computer scientist whose field of expertise is developing machine-learning methods for the life sciences. I received my PhD from Griffith University, Gold Coast, Australia in 2015 for my work on the prediction of stability and functional changes caused by genomic variants. After my PhD studies, I moved to Basel, Switzerland to continue my training as a postdoctoral fellow at ETH Zurich in the Machine Learning & Computational Biology Lab. There, my research focused on machine-learning methods for precision medicine. In 2018, I moved to Vienna, Austria to join CeMM Research Center for Molecular Medicine to develop machine-learning methods applicable to single-cell RNA-seq data analysis, for which I received European Commission's Marie Skłodowska-Curie Actions Postdoctoral Fellowship. While at CeMM, I also led a project studying epigenetic-immunological interplay and developed graph neural networks approaches for virtual screening of small molecules. In November 2022, I moved (back) to Griffith University to devote my efforts to developing deep-learning approaches for marine wildlife monitoring at the Coastal and Marine Research Centre.


  • E-mail.


  • applied machine learning and data science
  • computer vision for wildlife monitoring and ecology
  • bioinformatics for high-dimensional molecular data


Tools & downloads

  Kernelized rank learning for personalized drug recommendation

  Prediction of disease-causing genetic variants (indels, nonsense, and synonymous)

  Prediction of protein stability changes (ΔΔG) induced by protein mutations
Source code on GitHub      Datasets Web server      Singularity container Web server      Singularity container


# denotes equal contributions

  • de Bree LCJ, Mourits VP, Koeken VACM, Moorlag SJCFM, Janssen R, Folkman L, Barreca D, Krausgruber T, Fife-Gernedl V, Novakovic B, Arts RJW, Dijkstra H, Lemmers H, Bock C, Joosten LAB, van Crevel R, Benn CS & Netea MG (2020)
    Circadian rhythm influences induction of trained immunity by BCG vaccination
    The Journal of Clinical Investigation 130(10), 5603–5617
    📄 [Open access] [PubMed]
  • Pejaver V, Babbi G, Casadio R, Folkman L, Katsonis P, Kundu K, Lichtarge O, Martelli PL, Miller M, Moult J, Pal LR, Savojardo C, Yin Y, Zhou Y, Radivojac P & Bromberg Y (2019)
    Assessment of methods for predicting the effects of PTEN and TPMT protein variants
    Human Mutation 40(9), 1495–1506
    📄 [Article] [Open access via PMC] [PubMed] [CAGI5]
  • Savojardo C, Petrosino M, Babbi G, Bovo S, Corbi‐Verge C, Casadio R, Fariselli P, Folkman L, Garg A, Karimi M, Katsonis P, Kim PM, Lichtarge O, Martelli PL, Pasquo A, Pal D, Shen Y, Strokach AV, Turina P, Zhou Y, Andreoletti G, Brenner S, Chiaraluce R, Consalvi V & Capriotti E (2019)
    Evaluating the predictions of the protein stability change upon single amino acid substitutions for the FXN CAGI5 challenge
    Human Mutation 40(9), 1392–1399
    📄 [Article] [Open access via PMC] [PubMed] [CAGI5]
  • Clark WT, Kasak L, Bakolitsa C, Hu Z, Andreoletti G, Babbi G, Bromberg Y, Casadio R, Dunbrack R, Folkman L, Ford CT, Jones D, Katsonis P, Kundu K, Lichtarge O, Martelli PL, Mooney SD, Nodzak C, Pal LR, Radivojac P, Savojardo C, Shi X, Zhou Y, Uppal A, Xu Q, Yin Y, Pejaver V, Wang M, Wei L, Moult J, Yu GK, Brenner SE & LeBowitz JH (2019)
    Assessment of predicted enzymatic activity of alpha‐N‐acetylglucosaminidase (NAGLU) variants of unknown significance for CAGI 2016
    Human Mutation 40(9), 1519–1529
    📄 [Article] [Open access via PMC] [PubMed] [CAGI4]
  • He# X, Folkman# L & Borgwardt K (2018)
    Kernelized rank learning for personalized drug recommendation
    Bioinformatics 34(16), 2808–2816
    📄 [Open access] [Poster] [PubMed] [GitHub] [Datasets]
    ISMB/ECCB 2017 and [BC]2 2017 best poster awards
  • Livingstone# M, Folkman# L, Yang Y, Zhang P, Mort M, Cooper DN, Liu Y, Stantic B & Zhou Y (2017)
    Investigating DNA-, RNA-, and protein-based features as a means to discriminate pathogenic synonymous variants
    Human Mutation 38(10), 1336–1347
    📄 [Article] [Preprint] [PubMed] [Web server and datasets] [Singularity container]
  • Folkman L, Stantic B, Sattar A & Zhou Y (2016)
    EASE-MM: sequence-based prediction of mutation-induced stability changes with feature-based multiple models
    Journal of Molecular Biology, 428(6), 1394–1405
    📄 [Article] [Preprint] [PubMed] [Web server and datasets] [Singularity container]
    Ranked 3rd in the frataxin stability prediction during the Critical Assessment of Genome Interpretation 2018 competition
  • Folkman L, Yang Y, Li Z, Stantic B, Sattar B, Mort M, Cooper DN, Liu Y & Zhou Y (2015)
    DDIG-in: detecting disease-causing genetic variations due to frameshifting indels and nonsense mutations by sequence and structural properties at nucleotide and protein levels
    Bioinformatics 31(10), 1599–1606
    📄 [Open access] [PubMed] [Web server and datasets] [Singularity container]
    Winner of the Three Minutes Thesis Competition 2014 at the School of Information and Communication Technology, Griffith University
  • Folkman L, Stantic B & Sattar A (2014)
    Feature-based multiple models improve classification of mutation-induced stability changes
    BMC Genomics 15(Suppl 4), S6
    📄 [Open access] [PubMed]
  • Folkman L, Stantic B & Sattar A (2014)
    Towards sequence-based prediction of mutation-induced stability changes in unseen non-homologous proteins
    BMC Genomics 15(Suppl 1), S4
    📄 [Open access] [PubMed]
  • Folkman L, Stantic B & Sattar A (2013)
    Sequence-only evolutionary and predicted structural features for the prediction of stability changes in protein mutants
    BMC Bioinformatics 14(Suppl 2), S6
    📄 [Open access] [PubMed]
  • Higgs T, Folkman L & Stantic B (2013)
    Combining protein fragment feature-based resampling and local optimisation
    in ‘IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB)’, Vol. 7986 of LNCS, pp. 114–125, Springer
    📄 [Article]
  • Folkman L, Pullan W & Stantic B (2011)
    Generic parallel genetic algorithm framework for protein optimisation
    in ‘Algorithms and architectures for parallel processing (ICA3PP)’, Vol. 7017 of LNCS, pp. 64–73, Springer
    📄 [Article]
  • Stetsko A, Folkman L, & Matyas V (2010)
    Neighbor-based intrusion detection in wireless sensor networks
    in ‘Wireless and Mobile Communications (ICWMC)’, pp. 420–42, IEEE
    📄 [Article]