Blar i Bergen Open Research Archive på forfatter "Michoel, Tom"
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Causal inference in drug discovery and development
Michoel, Tom; Zhang, Jitao David (Journal article; Peer reviewed, 2023)To discover new drugs is to seek and to prove causality. As an emerging approach leveraging human knowledge and creativity, data, and machine intelligence, causal inference holds the promise of reducing cognitive bias and ... -
eQTLs as causal instruments for the reconstruction of hormone linked gene networks
Bankier, Sean Alexander; Michoel, Tom (Journal article; Peer reviewed, 2022)Hormones act within in highly dynamic systems and much of the phenotypic response to variation in hormone levels is mediated by changes in gene expression. The increase in the number and power of large genetic association ... -
A Graph Feature Auto-Encoder for the Prediction of Unobserved Node Features on Biological Networks
Hasibi, Ramin; Michoel, Tom (Journal article; Peer reviewed, 2021)Background Molecular interaction networks summarize complex biological processes as graphs, whose structure is informative of biological function at multiple scales. Simultaneously, omics technologies measure the variation ... -
Plasma cortisol linked gene networks in hepatic and adipose tissues implicate corticosteroid binding globulin in modulating tissue glucocorticoid action and cardiovascular risk
Bankier, Sean Alexander; Michoel, Tom (Journal article; Peer reviewed, 2023)Genome-wide association meta-analysis (GWAMA) by the Cortisol Network (CORNET) consortium identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14 associated with morning plasma cortisol, cardiovascular ... -
Restricted maximum-likelihood method for learning latent variance components in gene expression data with known and unknown confounders
Malik, Muhammad Ammar; Michoel, Tom (Journal article; Peer reviewed, 2022)Random effects models are popular statistical models for detecting and correcting spurious sample correlations due to hidden confounders in genome-wide gene expression data. In applications where some confounding factors ... -
Single-Cell Gene-Regulatory Networks of Advanced Symptomatic Atherosclerosis
Mocci, Giuseppe; Sukhavasi, Katyayani; Örd, Tiit; Bankier, Sean Alexander; Singha, Prosanta; Arasu, Uma Thanigai; Agbabiaje, Olayinka Oluwasegun; Mäkinen, Petri; Ma, Lijiang; Hodonsky, Chani J.; Aherrahrou, Redouane; Muhl, Lars; Liu, Jianping; Gustafsson, Sonja; Byandelger, Byambajav; Wang, Ying; Koplev, Simon; Lendahl, Urban; Owens, Gary K.; Leeper, Nicholas J.; Pasterkamp, Gerard; Vanlandewijck, Michael; Michoel, Tom; Ruusalepp, Arno; Hao, Ke; Ylä-Herttuala, Seppo; Väli, Marika; Järve, Heli; Mokry, Michal; Civelek, Mete; Miller, Clint J.; Kovacic, Jason C.; Kaikkonen, Minna U.; Betsholtz, Christer; Björkegren, Johan L.M. (Journal article; Peer reviewed, 2024)Background: While our understanding of the single-cell gene expression patterns underlying the transformation of vascular cell types during the progression of atherosclerosis is rapidly improving, the clinical and ... -
Use of big data and machine learning algorithms to extract possible treatment targets in neurodevelopmental disorders
Malik, Muhammad Ammar; Faraone, Stephen; Michoel, Tom; Haavik, Jan (Journal article; Peer reviewed, 2023)Neurodevelopmental disorders (NDDs) impact multiple aspects of an individual's functioning, including social interactions, communication, and behaviors. The underlying biological mechanisms of NDDs are not yet fully ...