Hanoch Kaphzan

2.6k total citations
50 papers, 1.9k citations indexed

About

Hanoch Kaphzan is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Hanoch Kaphzan has authored 50 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 25 papers in Genetics and 20 papers in Cellular and Molecular Neuroscience. Recurrent topics in Hanoch Kaphzan's work include Genetics and Neurodevelopmental Disorders (19 papers), Genetic Syndromes and Imprinting (16 papers) and Epigenetics and DNA Methylation (13 papers). Hanoch Kaphzan is often cited by papers focused on Genetics and Neurodevelopmental Disorders (19 papers), Genetic Syndromes and Imprinting (16 papers) and Epigenetics and DNA Methylation (13 papers). Hanoch Kaphzan collaborates with scholars based in Israel, United States and Japan. Hanoch Kaphzan's co-authors include Eric Klann, Philippe Pierre, Emanuela Santini, Aditi Bhattacharya, Kobi Rosenblum, Amanda Alvarez-Dieppa, Davide Ruggero, Andrew F. MacAskill, Adam G. Carter and Thu N. Huynh and has published in prestigious journals such as Nature, Nature Medicine and Neuron.

In The Last Decade

Hanoch Kaphzan

48 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hanoch Kaphzan Israel 20 1.1k 735 560 473 265 50 1.9k
Geeske M. van Woerden Netherlands 25 1.3k 1.2× 1.0k 1.4× 715 1.3× 391 0.8× 183 0.7× 49 2.3k
Michael J. Schmeißer Germany 23 922 0.8× 702 1.0× 555 1.0× 596 1.3× 253 1.0× 66 1.9k
Koko Ishizuka United States 21 1.4k 1.2× 431 0.6× 714 1.3× 247 0.5× 144 0.5× 59 2.5k
Tomoko Toyota Japan 31 1.5k 1.3× 850 1.2× 818 1.5× 398 0.8× 192 0.7× 87 2.8k
Alexander M. Kleschevnikov United States 27 1.0k 0.9× 1.0k 1.4× 752 1.3× 574 1.2× 192 0.7× 49 3.0k
Patrice L. Whitehead United States 21 798 0.7× 842 1.1× 281 0.5× 722 1.5× 147 0.6× 41 1.8k
Jae‐Ick Kim South Korea 17 836 0.8× 429 0.6× 846 1.5× 655 1.4× 130 0.5× 51 1.9k
Ioanna Konidari United States 17 625 0.6× 618 0.8× 329 0.6× 500 1.1× 153 0.6× 26 1.6k
Thomas Sander Germany 28 961 0.9× 565 0.8× 843 1.5× 369 0.8× 93 0.4× 52 2.2k
Timothy J. Jarome United States 29 984 0.9× 531 0.7× 942 1.7× 803 1.7× 115 0.4× 66 2.0k

Countries citing papers authored by Hanoch Kaphzan

Since Specialization
Citations

This map shows the geographic impact of Hanoch Kaphzan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hanoch Kaphzan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hanoch Kaphzan more than expected).

Fields of papers citing papers by Hanoch Kaphzan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hanoch Kaphzan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hanoch Kaphzan. The network helps show where Hanoch Kaphzan may publish in the future.

Co-authorship network of co-authors of Hanoch Kaphzan

This figure shows the co-authorship network connecting the top 25 collaborators of Hanoch Kaphzan. A scholar is included among the top collaborators of Hanoch Kaphzan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hanoch Kaphzan. Hanoch Kaphzan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Feuermann, Yonatan, et al.. (2025). Dynamic shift in localization of UBE3A across developmental stages in an Angelman syndrome mouse model. Neurobiology of Disease. 210. 106912–106912. 1 indexed citations
2.
Rathour, Rahul Kumar & Hanoch Kaphzan. (2024). Dendritic effects of tDCS insights from a morphologically realistic model neuron. iScience. 27(3). 109230–109230.
3.
Barak, Sharon, et al.. (2024). 1H-NMR-based metabolomics reveals metabolic alterations in early development of a mouse model of Angelman syndrome. Molecular Autism. 15(1). 31–31. 1 indexed citations
4.
Khatib, Soliman, et al.. (2024). Molecular Insights into Transcranial Direct Current Stimulation Effects: Metabolomics and Transcriptomics Analyses. Cells. 13(3). 205–205. 4 indexed citations
5.
Kaphzan, Hanoch, et al.. (2023). Direct Current Stimulation Modulates Synaptic Facilitation via Distinct Presynaptic Calcium Channels. International Journal of Molecular Sciences. 24(23). 16866–16866. 3 indexed citations
6.
Feuermann, Yonatan, et al.. (2023). Elevated ROS levels during the early development of Angelman syndrome alter the apoptotic capacity of the developing neural precursor cells. Molecular Psychiatry. 28(6). 2382–2397. 11 indexed citations
7.
Negev, Maya, et al.. (2023). Attitudes of psychiatrists toward telepsychiatry: A policy Delphi study. Digital Health. 9. 589820844–589820844. 2 indexed citations
8.
Kaphzan, Hanoch, et al.. (2022). The role of axonal voltage-gated potassium channels in tDCS. Brain stimulation. 15(3). 861–869. 6 indexed citations
9.
Kaphzan, Hanoch, et al.. (2022). An Association Study of DNA Methylation and Gene Expression in Angelman Syndrome: A Bioinformatics Approach. International Journal of Molecular Sciences. 23(16). 9139–9139. 2 indexed citations
10.
Getselter, Dmitriy, et al.. (2022). CTCF in parvalbumin-expressing neurons regulates motor, anxiety and social behavior and neuronal identity. Molecular Brain. 15(1). 30–30. 2 indexed citations
11.
Kaphzan, Hanoch, et al.. (2022). Calcium channels control tDCS-induced spontaneous vesicle release from axon terminals. Brain stimulation. 15(1). 270–282. 7 indexed citations
12.
Negev, Maya, et al.. (2021). Attitudinal Barriers Hindering Adoption of Telepsychiatry among Mental Healthcare Professionals: Israel as a Case-Study. International Journal of Environmental Research and Public Health. 18(23). 12540–12540. 5 indexed citations
13.
14.
Feuermann, Yonatan, et al.. (2020). Novel Insights into the Role of UBE3A in Regulating Apoptosis and Proliferation. Journal of Clinical Medicine. 9(5). 1573–1573. 18 indexed citations
15.
Feuermann, Yonatan, et al.. (2020). Bioinformatics Analyses of the Transcriptome Reveal Ube3a-Dependent Effects on Mitochondrial-Related Pathways. International Journal of Molecular Sciences. 21(11). 4156–4156. 13 indexed citations
16.
Sharvit, Lital, et al.. (2019). Sex-Dependent Sensory Phenotypes and Related Transcriptomic Expression Profiles Are Differentially Affected by Angelman Syndrome. Molecular Neurobiology. 56(9). 5998–6016. 25 indexed citations
17.
Sharma, Vijendra, Hadile Ounallah-Saad, Rapita Sood, et al.. (2017). Local Inhibition of PERK Enhances Memory and Reverses Age-Related Deterioration of Cognitive and Neuronal Properties. Journal of Neuroscience. 38(3). 648–658. 76 indexed citations
18.
Santini, Emanuela, et al.. (2015). Mitochondrial Superoxide Contributes to Hippocampal Synaptic Dysfunction and Memory Deficits in Angelman Syndrome Model Mice. Journal of Neuroscience. 35(49). 16213–16220. 54 indexed citations
19.
Bhattacharya, Aditi, et al.. (2012). Genetic Removal of p70 S6 Kinase 1 Corrects Molecular, Synaptic, and Behavioral Phenotypes in Fragile X Syndrome Mice. Neuron. 76(2). 325–337. 249 indexed citations
20.
Inoue, Keiichi, Hanoch Kaphzan, Eric Klann, et al.. (2012). Macroautophagy deficiency mediates age-dependent neurodegeneration through a phospho-tau pathway. Molecular Neurodegeneration. 7(1). 48–48. 139 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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