Mika Gustafsson

发表

Multi-resolution network modelling of T-cells for precision medicine of multiple sclerosis

Mika Gustafsson, 2017 .

Jämnhetsmätning på cykelvägar: utveckling och test av metod för att bedöma cyklisters åkkvalitet baserat på cykelvägens längsprofil

Anna Niska, Leif Sjögren, Mika Gustafsson, 2011 .

LASSIM - a network inference toolbox for genome-wide mechanistic modeling

Huan Zhang, Mika Gustafsson, Torbjörn E. M. Nordling, 2017, bioRxiv.

Correction to: A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases

Alex Arenas, Mika Gustafsson, Mattias Magnusson, 2020, Genome Medicine.

Soft Integration of Data for Reverse Engineering

Jesper Tegnér, Mika Gustafsson, Michael Hörnquist, 2008 .

ComHub: Community predictions of hubs in gene regulatory networks

Mika Gustafsson, Rasmus Magnusson, Julia Akesson, 2019, BMC Bioinformatics.

Comparison and validation of community structures in complex networks

Mika Gustafsson, Anna Lombardi, Michael Hornquist, 2006 .

Vägytans makrotextur och dess variation: vägytemätning med mätbil

Anita Ihs, Leif Sjögren, Thomas Lundberg, 2011 .

Digital twins to personalize medicine

Mika Gustafsson, Oleg Sysoev, Danuta R. Gawel, 2019, Genome Medicine.

LiPLike: towards gene regulatory network predictions of high certainty

Mika Gustafsson, Rasmus Magnusson, M. Gustafsson, 2020, Bioinformatics.

ModuleDiscoverer: Identification of regulatory modules in protein-protein interaction networks

Reinhard Guthke, Mika Gustafsson, Uta Dahmen, 2017 .

Gene expression prediction by the elastic net

Mika Gustafsson, Michael Hörnquist, 2008 .

LASSIM—A network inference toolbox for genome-wide mechanistic modeling

Huan Zhang, Rebecka Jörnsten, Gunnar Cedersund, 2017, bioRxiv.

Integrating various data sources for improved quality in reverse engineering of gene regulatory networks

Mika Gustafsson, Michael Hörnquist, 2009 .

MODifieR: an Ensemble R Package for Inference of Disease Modules from Transcriptomics Networks

Mika Gustafsson, David Martínez-Enguita, Zelmina Lubovac-Pilav, 2020, Bioinform..

In-silico network predictions by ODE and lasso

Mika Gustafsson, Michael Hörnquist, 2008 .

Combination of gene clusterings enhances biological validity

Mika Gustafsson, Michael Hörnquist, Anna Lombardi, 2004 .

Prognosmodeller för tillståndsmått i Trafikverkets Pavement Management System - makrotextur, MPD

Thomas Lundberg, Mika Gustafsson, Peter Andren, 2012 .

Systematic GWAS-assessment of disease modules reveals a multi-omic MS module strongly associated with risk factors

Maja Jagodic, Mika Gustafsson, David Martínez-Enguita, 2020, bioRxiv.

System Analysis of Gene Regulatory Networks

Mika Gustafsson, Michael Hörnquist, 2010 .

ModuleDiscoverer: Identification of regulatory modules in protein-protein interaction networks

Reinhard Guthke, Stefan Schuster, Mika Gustafsson, 2017, Scientific Reports.

Community structure in "gene-to-gene" networks

Mika Gustafsson, Anna Lombardi, Michael Hörnquist, 2004 .

Gene networks from high-throughput data -Reverse engineering and analysis

Mika Gustafsson, M. Gustafsson, 2010 .

Road user effect models : the influence of rut depth on traffic safety

Mats Wiklund, Anita Ihs, Leif Sjögren, 2011 .

Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder

Jesper Tegnér, Sanjiv K. Dwivedi, Mika Gustafsson, 2019, Nature Communications.

Deriving disease modules from the compressed transcriptional space embedded in a deep autoencoder

Jesper Tegnér, Sanjiv K. Dwivedi, Mika Gustafsson, 2020, Nature Communications.

LiPLike: towards gene regulatory network predictions of high certainty

Mika Gustafsson, Rasmus Magnusson, M. Gustafsson, 2019, bioRxiv.

ComHub: Community predictions of hubs in gene regulatory networks

Mika Gustafsson, Rasmus Magnusson, Zelmina Lubovac-Pilav, 2021, BMC Bioinform..

Using high-throughput multi-omics data to investigate structural balance in elementary gene regulatory network motifs

Claudio Altafini, Alberto Zenere, Mika Gustafsson, 2021, Bioinform..

Reverse Engineering of Gene Networks with LASSO and Nonlinear Basis Functions

Jesper Tegnér, Mika Gustafsson, Jesper Lundström, 2009, Annals of the New York Academy of Sciences.

DNA Methylation Changes Separate Allergic Patients from Healthy Controls and May Reflect Altered CD4+ T-Cell Population Structure

Michael A. Langston, Mika Gustafsson, Fredrik Barrenäs, 2014, PLoS genetics.

Cross-talks via mTORC2 can explain enhanced activation in response to insulin in diabetic patients

Gunnar Cedersund, Mika Gustafsson, Rasmus Magnusson, 2016, Bioscience reports.

Stability and Flexibility from a System Analysis of Gene Regulatory Networks Based on Ordinary Differential Equations

Mika Gustafsson, Michael Hörnquist, M. Gustafsson, 2011 .

5-Hydroxymethylcytosine Remodeling Precedes Lineage Specification during Differentiation of Human CD4(+) T Cells.

Bernward Klocke, Mika Gustafsson, Mikael Benson, 2016, Cell reports.

Gene Expression Prediction by Soft Integration and the Elastic Net—Best Performance of the DREAM3 Gene Expression Challenge

Mika Gustafsson, Michael Hörnquist, M. Gustafsson, 2010, PloS one.

A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases

Mika Gustafsson, Mikael Benson, Danuta R. Gawel, 2015, Science Translational Medicine.

Large-scale topology, stability and biology of gene networks

Mika Gustafsson, 2006 .

Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis.

Mika Gustafsson, Mikael Benson, Mattias Köpsén, 2016, Cell reports.

Modules, networks and systems medicine for understanding disease and aiding diagnosis

Pablo Villoslada, Albert-László Barabási, Mika Gustafsson, 2014, Genome Medicine.

A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases

Mika Gustafsson, Mikael Benson, Alex K. Shalek, 2019, Genome Medicine.