Thomas Van Parys

Thomas Van Parys — Staff
Joined the group in 2007

As a software engineer, I find myself very much at the 'informatics' side of 'bioinformatics'.
Over the wide range of projects I've been involved in, often at the visualization side of things, my programming language of choice is still Java, eg. for the Cytoscape Apps I have been developing or for the contributions to the early versions of GenomeView. For quick parsers and scripts, I turn to Python and Bash/Zsh, although I still often get excited about new tools and languages.

For web development, I've been using the CakePHP (+JQuery) MVC framework for webtool projects of different sizes (eg. Orcae, hfAIM, ...) and Drupal for CMS websites (like the one you're looking at right now).

As part of my sysadmin duties I maintain our local Apache webserver(s) and MySQL databases.
Being an avid GNU/Linux user and offering IT support to this group did make me into a zealous proponent of Linux on the desktop and git code versioning.
And Emacs of course. Don't forget Emacs.

Birthdate: 19 November 1980, Gent, Belgium.

  • 2012 : Software development at BEG (VIB / Ghent University)
  • 2011 - 2012: Visiting scientist at FMG (University of Pretoria)
  • 2007 - 2011: Software development at BEG (VIB / Ghent University)
  • 2005 - 2007: Webmaster HiPEAC (ELIS - Ghent University)
  • 2003 - 2005: Master Computer Sciences (Software Development) at Ghent University
  • 1999 - 2003: Industrial Engineering (IT) at Hogeschool Gent

Publications

  1. Van Parys, T., Melckenbeeck, I., Houbraken, M., Audenaert, P., Colle, D., Pickavet, M., Demeester, P., et al. (2017). A Cytoscape app for motif enumeration with ISMAGS. BIOINFORMATICS, 33(3), 461–463.
    We present a Cytoscape app for the ISMAGS algorithm, which can enumerate all instances of a motif in a graph, making optimal use of the motif's symmetries to make the search more efficient. The Cytoscape app provides a handy interface for this algorithm, which allows more efficient network analysis.
  2. Van Landeghem, S., Van Parys, T., Dubois, M., Inzé, D., & Van de Peer, Y. (2016). Diffany: an ontology-driven framework to infer, visualise and analyse differential molecular networks. BMC BIOINFORMATICS, 17.
    Background: Differential networks have recently been introduced as a powerful way to study the dynamic rewiring capabilities of an interactome in response to changing environmental conditions or stimuli. Currently, such differential networks are generated and visualised using ad hoc methods, and are often limited to the analysis of only one condition-specific response or one interaction type at a time. Results: In this work, we present a generic, ontology-driven framework to infer, visualise and analyse an arbitrary set of condition-specific responses against one reference network. To this end, we have implemented novel ontology-based algorithms that can process highly heterogeneous networks, accounting for both physical interactions and regulatory associations, symmetric and directed edges, edge weights and negation. We propose this integrative framework as a standardised methodology that allows a unified view on differential networks and promotes comparability between differential network studies. As an illustrative application, we demonstrate its usefulness on a plant abiotic stress study and we experimentally confirmed a predicted regulator. Availability: Diffany is freely available as open-source java library and Cytoscape plugin from http://bioinformatics.psb.ugent.be/supplementary_data/solan/diffany/.
  3. Xie, Qingjun, Tzfadia, O., Levy, M., Weithorn, E., Peled-Zehavi, H., Van Parys, T., Van de Peer, Y., et al. (2016). hfAIM: a reliable bioinformatics approach for in silico genome-wide identification of autophagy-associated Atg8-interacting motifs in various organisms. AUTOPHAGY, 12(5), 876–887.
    Most of the proteins that are specifically turned over by selective autophagy are recognized by the presence of short Atg8 interacting motifs (AIMs) that facilitate their association with the autophagy apparatus. Such AIMs can be identified by bioinformatics methods based on their defined degenerate consensus F/W/Y-X-X-L/I/V sequences in which X represents any amino acid. Achieving reliability and/or fidelity of the prediction of such AIMs on a genome-wide scale represents a major challenge. Here, we present a bioinformatics approach, high fidelity AIM (hfAIM), which uses additional sequence requirementsthe presence of acidic amino acids and the absence of positively charged amino acids in certain positionsto reliably identify AIMs in proteins. We demonstrate that the use of the hfAIM method allows for in silico high fidelity prediction of AIMs in AIM-containing proteins (ACPs) on a genome-wide scale in various organisms. Furthermore, by using hfAIM to identify putative AIMs in the Arabidopsis proteome, we illustrate a potential contribution of selective autophagy to various biological processes. More specifically, we identified 9 peroxisomal PEX proteins that contain hfAIM motifs, among which AtPEX1, AtPEX6 and AtPEX10 possess evolutionary-conserved AIMs. Bimolecular fluorescence complementation (BiFC) results verified that AtPEX6 and AtPEX10 indeed interact with Atg8 in planta. In addition, we show that mutations occurring within or nearby hfAIMs in PEX1, PEX6 and PEX10 caused defects in the growth and development of various organisms. Taken together, the above results suggest that the hfAIM tool can be used to effectively perform genome-wide in silico screens of proteins that are potentially regulated by selective autophagy. The hfAIM system is a web tool that can be accessed at link: http://bioinformatics.psb.ugent.be/hfAIM/.
  4. Vermeirssen, Vanessa, De Clercq, I., Van Parys, T., Van Breusegem, F., & Van de Peer, Y. (2014). Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress. PLANT CELL, 26(12), 4656–4679.
    The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain-and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation.
  5. Abeel, T., Van Parys, T., Saeys, Y., Galagan, J., & Van de Peer, Y. (2012). GenomeView: a next-generation genome browser. NUCLEIC ACIDS RESEARCH, 40(2).
    Due to ongoing advances in sequencing technologies, billions of nucleotide sequences are now produced on a daily basis. A major challenge is to visualize these data for further downstream analysis. To this end, we present GenomeView, a stand-alone genome browser specifically designed to visualize and manipulate a multitude of genomics data. GenomeView enables users to dynamically browse high volumes of aligned short-read data, with dynamic navigation and semantic zooming, from the whole genome level to the single nucleotide. At the same time, the tool enables visualization of whole genome alignments of dozens of genomes relative to a reference sequence. GenomeView is unique in its capability to interactively handle huge data sets consisting of tens of aligned genomes, thousands of annotation features and millions of mapped short reads both as viewer and editor. GenomeView is freely available as an open source software package.
  6. Kano, Y., Bjorne, J., Ginter, F., Salakoski, T., Buyko, E., Hahn, U., Cohen, K., et al. (2011). U-Compare bio-event meta-service: compatible BioNLP event extraction services. BMC BIOINFORMATICS, 12.
    Background: Bio-molecular event extraction from literature is recognized as an important task of bio text mining and, as such, many relevant systems have been developed and made available during the last decade. While such systems provide useful services individually, there is a need for a meta-service to enable comparison and ensemble of such services, offering optimal solutions for various purposes. Results: We have integrated nine event extraction systems in the U-Compare framework, making them inter-compatible and interoperable with other U-Compare components. The U-Compare event meta-service provides various meta-level features for comparison and ensemble of multiple event extraction systems. Experimental results show that the performance improvements achieved by the ensemble are significant. Conclusions: While individual event extraction systems themselves provide useful features for bio text mining, the U-Compare meta-service is expected to improve the accessibility to the individual systems, and to enable meta-level uses over multiple event extraction systems such as comparison and ensemble.
  7. Audenaert, P., Van Parys, T., Brondel, F., Pickavet, M., Demeester, P., Van de Peer, Y., & Michoel, T. (2011). CyClus3D: a Cytoscape plugin for clustering network motifs in integrated networks. BIOINFORMATICS, 27(11), 1587–1588.
    Network motifs in integrated molecular networks represent functional relationships between distinct data types. They aggregate to form dense topological structures corresponding to functional modules which cannot be detected by traditional graph clustering algorithms. We developed CyClus3D, a Cytoscape plugin for clustering composite three-node network motifs using a 3D spectral clustering algorithm.
  8. Joshi, A. M., Van Parys, T., Van de Peer, Y., & Michoel, T. (2010). Characterizing regulatory path motifs in integrated networks using perturbational data. GENOME BIOLOGY, 11(3).
    We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks. Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data. A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.
  9. Proost, Sebastian, Van Bel, M., Sterck, L., Billiau, K., Van Parys, T., Van de Peer, Y., & Vandepoele, K. (2009). PLAZA: a comparative genomics resource to study gene and genome evolution in plants. PLANT CELL, 21(12), 3718–3731.
    The number of sequenced genomes of representatives within the green lineage is rapidly increasing. Consequently, comparative sequence analysis has significantly altered our view on the complexity of genome organization, gene function, and regulatory pathways. To explore all this genome information, a centralized infrastructure is required where all data generated by different sequencing initiatives is integrated and combined with advanced methods for data mining. Here, we describe PLAZA, an online platform for plant comparative genomics (http://bioinformatics.psb.ugent.be/plaza/). This resource integrates structural and functional annotation of published plant genomes together with a large set of interactive tools to study gene function and gene and genome evolution. Precomputed data sets cover homologous gene families, multiple sequence alignments, phylogenetic trees, intraspecies whole-genome dot plots, and genomic colinearity between species. Through the integration of high confidence Gene Ontology annotations and tree-based orthology between related species, thousands of genes lacking any functional description are functionally annotated. Advanced query systems, as well as multiple interactive visualization tools, are available through a user-friendly and intuitive Web interface. In addition, detailed documentation and tutorials introduce the different tools, while the workbench provides an efficient means to analyze user-defined gene sets through PLAZA's interface. In conclusion, PLAZA provides a comprehensible and up-to-date research environment to aid researchers in the exploration of genome information within the green plant lineage.

Other publications

  1. Artaza H, Chue Hong N, Corpas M et al. Top 10 metrics for life science software good practices. F1000Research 2016, 5(ELIXIR):2000