Andreas Tjärnberg

发表

Cancer network activity associated with therapeutic response and synergism

M. Ferrer, M. Esteller, P. Aloy, 2016, Genome Medicine.

Exploring the Boundaries of Gene Regulatory Network Inference

Andreas Tjärnberg, 2015 .

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.

Comparative interactomics with Funcoup 2.0

Andrey Alexeyenko, Erik L. L. Sonnhammer, Dimitri Guala, 2011, Nucleic Acids Res..

Influence of probiotic treatment on allergy methylomics Gene network analysis of epigenetic methylation patterns in CD 4 + T cells from newborns treated with Lactobacillus reuteri

Andreas Tjärnberg, Mika Gustafsson Tutor, 2018 .

High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0

Dayanne M. Castro, D. Gresham, Emily R. Miraldi, 2022, Bioinformatics.

Structure primed embedding on the transcription factor manifold enables transparent model architectures for gene regulatory network and latent activity inference

D. Gresham, R. Bonneau, L. Christiaen, 2023, bioRxiv.

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

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

Optimal Sparsity Criteria for Network Inference

Erik L. L. Sonnhammer, Torbjörn E. M. Nordling, Andreas Tjärnberg, 2013, J. Comput. Biol..

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

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

Uncovering cancer gene regulation by accurate regulatory network inference from uninformative data

Torbjörn E. M. Nordling, E. Sonnhammer, S. Nelander, 2020, npj Systems Biology and Applications.

Uncovering cancer gene regulation by accurate regulatory network inference from uninformative data

Torbjörn E. M. Nordling, E. Sonnhammer, S. Nelander, 2020, NPJ systems biology and applications.

High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0

Dayanne M. Castro, N. Carriero, D. Gresham, 2021, bioRxiv.

Avoiding pitfalls in L1-regularised inference of gene networks.

Torbjörn E. M. Nordling, Erik L L Sonnhammer, Andreas Tjärnberg, 2015, Molecular bioSystems.

Perturbation-based gene regulatory network inference to unravel oncogenic mechanisms

Erik L. L. Sonnhammer, Torbjörn E. M. Nordling, Andreas Tjärnberg, 2019, Scientific Reports.

The Complex Genetics of Multiple Sclerosis A preliminary study of MS-associated SNPs prior to a larger genotyping project

Andreas Tjärnberg, Examinator, 2016 .

Functional association networks as priors for gene regulatory network inference

Erik L. L. Sonnhammer, Torbjörn E. M. Nordling, Andreas Tjärnberg, 2014, Bioinform..

GeneSPIDER - gene regulatory network inference benchmarking with controlled network and data properties.

Torbjörn E. M. Nordling, Erik L L Sonnhammer, Andreas Tjärnberg, 2017, Molecular bioSystems.

A generalized framework for controlling FDR in gene regulatory network inference

Erik L. L. Sonnhammer, Torbjörn E. M. Nordling, Andreas Tjärnberg, 2018, Bioinform..

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

Colm E. Nestor, Eun Jung Lee, A. Shalek, 2019, Genome Medicine.

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

Eun Jung Lee, A. Shalek, M. Benson, 2020, Genome Medicine.

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

Huan Zhang, Rebecka Jörnsten, Gunnar Cedersund, 2017, PLoS Comput. Biol..

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

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

GeneSPIDER - Generation and Simulation Package for Informative Data ExploRation

Erik L. L. Sonnhammer, Torbjörn E. M. Nordling, Andreas Tjärnberg, 2015 .

Knowledge of the perturbation design is essential for accurate gene regulatory network inference

Torbjörn E. M. Nordling, E. Sonnhammer, Andreas Tjärnberg, 2022, Scientific Reports.

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.