Author

Alex Hakansson

Sanford Burnham Prebys Medical Discovery Institute

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 3 Research Focus:differential expression· 3 Organism:human· 3 Research Focus:clustering· 2 Approach:experimental assay· 2 Assay:scRNA-seq· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1

Frequent Co-Authors

Carlo PiermarocchiiD· 2 shared Giovanni PaternostroiD· 2 shared Sergii DomanskyiiD· 2 shared Andrea SboneriD· 1 shared Benjamin K. PhamiD· 1 shared Brian D. RobinsoniD· 1 shared Christopher E. BarbieriiD· 1 shared Deli LiuiD· 1 shared

Activity by Year

2021-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersSystems Biology

Carlo PiermarocchiORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Canonical AREs are tumor suppressive regulatory elements in the prostate

Xuanrong Chen, Michael A. Augello, Deli Liu, Kevin Lin, Alex Hakansson, Martin Sjöström, Francesca Khani, Lesa Dayal Deonarine, Yang Liu, Jaida Travascio-Green, Jiansheng Wu, Un In Chan, Jude N. Owiredu, Massimo F. Loda, Felix Yi-Chung Feng, , Christopher E. Barbieri

This study identifies canonical AREs as tumor suppressive regulatory elements in prostate cancer, showing their reactivation can induce death in AR+ cancer cells and is linked to better prognosis.

Nature Communications · Dec 13, 2024Peer-reviewedCancer Biology

Naturally occurring combinations of receptors from single cell transcriptomics in endothelial cells

Sergii Domanskyi, Alex Hakansson, Michelle Y. Meng, Benjamin K. Pham, Joshua Graff Zivin, Carlo Piermarocchi, Giovanni Paternostro, Napoleone Ferrara

The paper identifies naturally occurring receptor combinations in endothelial cells using single-cell data and introduces a software tool to analyze them, showing evolutionary conservation and relevance to angiogenesis.

Scientific Reports · Apr 6, 2022Peer-reviewedSystems Biology

Digital Cell Sorter (DCS): a cell type identification, anomaly detection, and Hopfield landscapes toolkit for single-cell transcriptomics

Sergii Domanskyi, Alex Hakansson, Thomas J. Bertus, Giovanni Paternostro, Carlo Piermarocchi

The paper introduces DCS, a toolkit for scRNA-seq analysis that includes cell type identification, anomaly detection, and visualization tools, demonstrating its effectiveness on PBMC and plasma cell datasets.

PeerJ · Jan 13, 2021Peer-reviewedBioinformatics