Daniel T.S. Pak

6.1k total citations · 1 hit paper
70 papers, 5.1k citations indexed

About

Daniel T.S. Pak is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Physiology. According to data from OpenAlex, Daniel T.S. Pak has authored 70 papers receiving a total of 5.1k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Cellular and Molecular Neuroscience, 35 papers in Molecular Biology and 18 papers in Physiology. Recurrent topics in Daniel T.S. Pak's work include Neuroscience and Neuropharmacology Research (48 papers), Alzheimer's disease research and treatments (17 papers) and Neurogenesis and neuroplasticity mechanisms (10 papers). Daniel T.S. Pak is often cited by papers focused on Neuroscience and Neuropharmacology Research (48 papers), Alzheimer's disease research and treatments (17 papers) and Neurogenesis and neuroplasticity mechanisms (10 papers). Daniel T.S. Pak collaborates with scholars based in United States, South Korea and Italy. Daniel T.S. Pak's co-authors include Morgan Sheng, Jerry W. Shay, Walter D. Funk, Richard H. Karas, Woodring E. Wright, Michael R. Botchan, Hyang‐Sook Hoe, So‐Young Yang, Eunjoon Kim and Daniel P. Seeburg and has published in prestigious journals such as Science, Cell and Journal of Biological Chemistry.

In The Last Decade

Daniel T.S. Pak

70 papers receiving 5.0k citations

Hit Papers

A transcriptionally active DNA-binding site for human p53... 1992 2026 2003 2014 1992 200 400 600

Peers

Daniel T.S. Pak
Raymond J. Kelleher United States
Vladimir L. Buchman United Kingdom
John R. Hepler United States
Natalia Ninkina United Kingdom
Robby M. Weimer United States
Russell T. Matthews United States
Raymond J. Kelleher United States
Daniel T.S. Pak
Citations per year, relative to Daniel T.S. Pak Daniel T.S. Pak (= 1×) peers Raymond J. Kelleher

Countries citing papers authored by Daniel T.S. Pak

Since Specialization
Citations

This map shows the geographic impact of Daniel T.S. Pak'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 Daniel T.S. Pak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T.S. Pak more than expected).

Fields of papers citing papers by Daniel T.S. Pak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel T.S. Pak. 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 Daniel T.S. Pak. The network helps show where Daniel T.S. Pak may publish in the future.

Co-authorship network of co-authors of Daniel T.S. Pak

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel T.S. Pak. A scholar is included among the top collaborators of Daniel T.S. Pak 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 Daniel T.S. Pak. Daniel T.S. Pak 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.
Lee, Jisoo & Daniel T.S. Pak. (2024). Amyloid precursor protein combinatorial phosphorylation code regulates AMPA receptor removal during distinct forms of synaptic plasticity. Biochemical and Biophysical Research Communications. 709. 149803–149803. 2 indexed citations
2.
Zhu, William, et al.. (2024). Mass spectrometry identifies tau C‐terminal phosphorylation cluster during neuronal hyperexcitation. Journal of Neurochemistry. 169(1). e16221–e16221. 1 indexed citations
3.
Pak, Daniel T.S., et al.. (2023). Wherefore Art Tau? Functional importance of site-specific tau phosphorylation in diverse subcellular domains. The International Journal of Biochemistry & Cell Biology. 164. 106475–106475. 1 indexed citations
4.
Pak, Daniel T.S., et al.. (2023). Plk2 promotes synaptic destabilization through disruption of N‐cadherin adhesion complexes during homeostatic adaptation to hyperexcitation. Journal of Neurochemistry. 167(3). 362–375. 1 indexed citations
5.
Pak, Daniel T.S., et al.. (2022). ACh Transfers: Homeostatic Plasticity of Cholinergic Synapses. Cellular and Molecular Neurobiology. 43(2). 697–709. 6 indexed citations
6.
Pak, Daniel T.S., et al.. (2020). Central Cholinergic Synapse Formation in Optimized Primary Septal-Hippocampal Co-cultures. Cellular and Molecular Neurobiology. 41(8). 1787–1799. 5 indexed citations
7.
Caccavano, Adam, P. Lorenzo Bozzelli, Patrick A. Forcelli, et al.. (2020). Inhibitory Parvalbumin Basket Cell Activity is Selectively Reduced during Hippocampal Sharp Wave Ripples in a Mouse Model of Familial Alzheimer's Disease. Journal of Neuroscience. 40(26). 5116–5136. 55 indexed citations
8.
Chen, Xin, et al.. (2019). Activation of nicotinic acetylcholine receptors induces potentiation and synchronization within in vitro hippocampal networks. Journal of Neurochemistry. 153(4). 468–484. 9 indexed citations
9.
Song, Jung Min, You Me Sung, Taehee Lee, et al.. (2015). Hexa (ethylene glycol) derivative of benzothiazole aniline promotes dendritic spine formation through the RasGRF1–Ras dependent pathway. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1862(2). 284–295. 9 indexed citations
10.
Lee, Kea Joo, Im Joo Rhyu, & Daniel T.S. Pak. (2014). Synapses need coordination to learn motor skills. Reviews in the Neurosciences. 25(2). 223–30. 6 indexed citations
11.
Song, Jung Min, Amanda M. DiBattista, You Me Sung, et al.. (2013). A tetra(ethylene glycol) derivative of benzothiazole aniline ameliorates dendritic spine density and cognitive function in a mouse model of Alzheimer's disease. Experimental Neurology. 252. 105–113. 30 indexed citations
12.
Shin, Seung Min, Nanyan Zhang, Nashaat Z. Gerges, et al.. (2012). GKAP orchestrates activity-dependent postsynaptic protein remodeling and homeostatic scaling. Nature Neuroscience. 15(12). 1655–1666. 102 indexed citations
13.
Babus, Lenard W., Sakura Minami, Jung Min Song, et al.. (2011). Decreased dendritic spine density and abnormal spine morphology in Fyn knockout mice. Brain Research. 1415. 96–102. 30 indexed citations
14.
Rogers, Justin, Justin H. Trotter, Daniel T.S. Pak, et al.. (2011). Reelin supplementation enhances cognitive ability, synaptic plasticity, and dendritic spine density. Learning & Memory. 18(9). 558–564. 143 indexed citations
15.
Lee, Kyung‐Jin, Charbel Moussa, Young Ju Lee, et al.. (2010). Beta amyloid-independent role of amyloid precursor protein in generation and maintenance of dendritic spines. Neuroscience. 169(1). 344–356. 101 indexed citations
16.
Hoe, Hyang‐Sook, Hey‐Kyoung Lee, & Daniel T.S. Pak. (2010). The Upside of APP at Synapses. CNS Neuroscience & Therapeutics. 18(1). 47–56. 68 indexed citations
17.
Hoe, Hyang‐Sook, Kyung‐Jin Lee, Rosalind S.E. Carney, et al.. (2009). Interaction of Reelin with Amyloid Precursor Protein Promotes Neurite Outgrowth. Journal of Neuroscience. 29(23). 7459–7473. 174 indexed citations
18.
Hoe, Hyang‐Sook, Matthew J. Cooper, Mark P. Burns, et al.. (2007). The Metalloprotease Inhibitor TIMP-3 Regulates Amyloid Precursor Protein and Apolipoprotein E Receptor Proteolysis. Journal of Neuroscience. 27(40). 10895–10905. 61 indexed citations
19.
Richter, Melanie, et al.. (2007). The EphA4 Receptor Regulates Neuronal Morphology through SPAR-Mediated Inactivation of Rap GTPases. Journal of Neuroscience. 27(51). 14205–14215. 70 indexed citations
20.
Zhu, Yinghua, Daniel T.S. Pak, Yi Qin, et al.. (2005). Rap2-JNK Removes Synaptic AMPA Receptors during Depotentiation. Neuron. 47(2). 321–321. 1 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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