Author

Christin Andersson

Donostiako Unibertsitate Ospitalea

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

Biology Disciplines

Click to filter author papers

Neuroscience· 2

Signature Assays, Organisms & Methods

Click to filter · or open tag

Research Focus:differential expression· 2 Organism:human· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:clustering· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Alessandro PadovaniiD· 2 shared Alexandre de MendonçaiD· 2 shared Andrea ArighiiD· 2 shared Barbara BorroniiD· 2 shared Caroline GraffiD· 2 shared Chiara FenoglioiD· 2 shared Daniela GalimbertiiD· 2 shared David Lee ThomasiD· 2 shared

Activity by Year

2018-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersNeuroscience

Alessandro PadovaniORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Analysis of brain atrophy and local gene expression in genetic frontotemporal dementia

André Altmann, David M. Cash, Martina Bocchetta, Carolin Heller, Regina Hertfelder Reynolds, Katrina M. Moore, Rhian S. Convery, David Lee Thomas, John Cornelis Van Swieten, Fermín Moreno, Raquel Sánchez‐Valle, Barbara Borroni, Robert Jr Laforce, Mario Masellis, Maria Carmela Tartaglia, , Philip Van Damme

The paper investigates the relationship between gene expression and brain atrophy in genetic frontotemporal dementia, finding correlations between atrophy patterns and specific gene sets related to vascular, glial, and neuronal functions.

Brain Communications · Jan 1, 2020Peer-reviewedNeuroscience

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

Alexandra L. Young, Razvan Valentin Marinescu, Neil P. Oxtoby, Martina Bocchetta, Keir X. X. Yong, Nicholas C. Firth, David M. Cash, David Lee Thomas, Katrina M. Dick, M. Jorge Cardoso, John Cornelis Van Swieten, Barbara Borroni, Daniela Galimberti, Mario Masellis, Maria Carmela Tartaglia, , Ronald G. Thomas

This paper introduces SuStaIn, a machine learning method that identifies disease subtypes and their temporal progression from cross-sectional data, improving prediction of diagnostic conversion in neurodegenerative diseases.

Nature Communications · Oct 9, 2018Peer-reviewedNeuroscience