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      University of Skövde, link to startpage
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      2. About us

      Hendrik de Weerd

      PhD Student Bioinformatics
      School of Bioscience
      Room G2249
      e-mail hendrik.arnold.de.weerd@his.se
      Phone 0500-448649

      Research

      2022

      MODalyseR—a novel software for inference of disease module hub regulators identified a putative multiple sclerosis regulator supported by independent eQTL data

      Hendrik A. de Weerd, Julia Åkesson, Dimitri Guala, Mika Gustafsson, Zelmina Lubovac-Pilav

      Bioinformatics Advances

      2022. Article. https://doi.org/10.1093/bioadv/vbac006 Open Access

      DLG2 impairs dsDNA break repair and maintains genome integrity in neuroblastoma

      Simon Keane, Hendrik Arnold de Weerd, Katarina Ejeskär

      DNA Repair

      2022. Article. https://doi.org/10.1016/j.dnarep.2022.103302 Open Access

      2021

      A validated generally applicable approach using the systematic assessment of disease modules by GWAS reveals a multi-omic module strongly associated with risk factors in multiple sclerosis

      Tejaswi V. S. Badam, Hendrik A. de Weerd, David Martínez-Enguita, Tomas Olsson, Lars Alfredsson, Ingrid Kockum, Maja Jagodic, Zelmina Lubovac-Pilav, Mika Gustafsson

      BMC Genomics

      2021. Article. https://doi.org/10.1186/s12864-021-07935-1 Open Access

      2020

      MODifieR: an ensemble R package for inference of disease modules from transcriptomics networks

      Hendrik A. de Weerd, Tejaswi V. S. Badam, David Martínez-Enguita, Julia Åkesson, Daniel Muthas, Mika Gustafsson, Zelmina Lubovac-Pilav

      Bioinformatics

      2020. Article. https://doi.org/10.1093/bioinformatics/btaa235 Open Access

      2019

      miRFA: an automated pipeline for microRNA functional analysis with correlation support from TCGA and TCPA expression data in pancreatic cancer

      Emmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav, Malin Sund

      BMC Bioinformatics

      2019. Article. https://doi.org/10.1186/s12859-019-2974-3 Open Access

      2018

      NIPTeR: an R package for fast and accurate trisomy prediction in non-invasive prenatal testing

      Lennart F. Johansson, Hendrik A. de Weerd, Eddy N. de Boer, Freerk van Dijk, Gerard J. Te Meerman, Rolf H. Sijmons, Birgit Sikkema-Raddatz, Morris A. Swertz

      BMC Bioinformatics

      2018. Article. https://doi.org/10.1186/s12859-018-2557-8 Open Access

      October 2020 - September 2024 Systems Biology
      Published: 1/9/2020
      Edited: 1/9/2020
      Responsible: webmaster@his.se