Author

Hagit Hochner

Hebrew University of JerusalemORCID 0000-0002-8853-2276Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Genomics· 1 Pathology· 1

Signature Assays, Organisms & Methods

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Organism:human· 4 Approach:deep learning· 3 Research Focus:differential expression· 3 Research Focus:benchmarking· 2 Research Focus:cell type annotation· 2 Research Focus:clustering· 2 Assay:imaging· 2 Assay:DNA methylation· 1

Frequent Co-Authors

Cecilia M. LindgreniD· 2 shared Christoffer NellåkeriD· 2 shared Claudia VaneaiD· 2 shared Drorith Hochner‐CelnikieriD· 2 shared Karen S. Meir· 2 shared Linda M. ErnstiD· 2 shared Triin LaiskiD· 2 shared Yechiel FriedlanderiD· 2 shared

Activity by Year

2018-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersPathology

Cecilia M. LindgrenORCID

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Author profile →

4 papers

Recent·Most cited

Biologically-Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types

Emma Clare Walker, Claudia Vanea, Karen S. Meir, Drorith Hochner‐Celnikier, Hagit Hochner, Triin Laisk, Cecilia M. Lindgren, Craig A. Glastonbury, Linda M. Ernst, Christoffer Nellåker

The paper uses a deep learning pipeline to analyze placental histology and identifies cellular and structural changes across different lesion types.

Placenta · Apr 1, 2026Peer-reviewedPathology

Time is encoded by methylation changes at clustered CpG sites

Bracha-Lea Ochana, Daniel Nudelman, Daniel Cohen, Ayelet Peretz, Sheina Piyanzin, Ofer Gal-Rosenberg, Amit Horn, Netanel Loyfer, Miri Varshavsky, Ron Raisch, Ilona Shapiro, Yechiel Friedlander, Hagit Hochner, Benjamin Gläser, Yuval Dor, , Ruth Shemer

The paper shows that DNA methylation changes at clustered CpG sites encode chronological age with high accuracy using deep learning on blood samples.

Cell Reports · Jul 1, 2025Peer-reviewedGenomics

HAPPY: A deep learning pipeline for mapping cell-to-tissue graphs across placenta histology whole slide images

Claudia Vanea, Jelisaveta Džigurski, Valentina Rukins, Omri Dodi, Siim Siigur, Liis Salumäe, Karen S. Meir, William Tony Parks, Drorith Hochner‐Celnikier, Abigail Fraser, Hagit Hochner, Triin Laisk, Linda M. Ernst, Cecilia M. Lindgren, Christoffer Nellåker

HAPPY quantifies cell and tissue variability in placenta histology images, providing metrics that align with clinical experts and reveal deviations in placental infarction.

bioRxiv · Nov 21, 2022 · PreprintBioinformatics

A study of Kibbutzim in Israel reveals risk factors for cardiometabolictraits and subtle population structure

Einat Granot‐Hershkovitz, David Karasik, Yechiel Friedlander, Laura Rodriguez‐Murillo, Rajkumar Dorajoo, Jianjun Liu, Anshuman Sewda, Inga Peter, Shai Carmi, Hagit Hochner

The paper analyzes genetic and environmental factors in Israeli kibbutzim to identify cardiometabolic trait associations and population structure.

European Journal of Human Genetics · Aug 14, 2018Peer-reviewedGenetics