Tammy Gillis

7.3k total citations
36 papers, 1.9k citations indexed

About

Tammy Gillis is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Neurology. According to data from OpenAlex, Tammy Gillis has authored 36 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Cellular and Molecular Neuroscience, 31 papers in Molecular Biology and 15 papers in Neurology. Recurrent topics in Tammy Gillis's work include Genetic Neurodegenerative Diseases (33 papers), Mitochondrial Function and Pathology (25 papers) and Neurological disorders and treatments (13 papers). Tammy Gillis is often cited by papers focused on Genetic Neurodegenerative Diseases (33 papers), Mitochondrial Function and Pathology (25 papers) and Neurological disorders and treatments (13 papers). Tammy Gillis collaborates with scholars based in United States, Portugal and Canada. Tammy Gillis's co-authors include Vanessa C. Wheeler, James F. Gusella, Marcy E. MacDonald, Jong‐Min Lee, Jayalakshmi Srinidhi Mysore, Richard H. Myers, Audrey E. Hendricks, Ella Dragileva, Michael J. Chao and Edith Lopez and has published in prestigious journals such as Science, Nature Communications and PLoS ONE.

In The Last Decade

Tammy Gillis

35 papers receiving 1.9k citations

Peers

Tammy Gillis
Antoni Matilla‐Dueñas Spain
Paymaan Jafar‐Nejad United States
Jong‐Min Lee United States
David Soto Spain
Dineke S. Verbeek Netherlands
Manu Sharma Germany
Una‐Marie Sheerin United Kingdom
Francesca Persichetti Italy
Kellie Benzow United States
Astrid Lunkes Germany
Antoni Matilla‐Dueñas Spain
Tammy Gillis
Citations per year, relative to Tammy Gillis Tammy Gillis (= 1×) peers Antoni Matilla‐Dueñas

Countries citing papers authored by Tammy Gillis

Since Specialization
Citations

This map shows the geographic impact of Tammy Gillis'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 Tammy Gillis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tammy Gillis more than expected).

Fields of papers citing papers by Tammy Gillis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tammy Gillis. 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 Tammy Gillis. The network helps show where Tammy Gillis may publish in the future.

Co-authorship network of co-authors of Tammy Gillis

This figure shows the co-authorship network connecting the top 25 collaborators of Tammy Gillis. A scholar is included among the top collaborators of Tammy Gillis 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 Tammy Gillis. Tammy Gillis 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.
Gao, Dadi, Kevin Correia, Jennie C. L. Roy, et al.. (2024). Splice modulators target PMS1 to reduce somatic expansion of the Huntington’s disease-associated CAG repeat. Nature Communications. 15(1). 3182–3182. 14 indexed citations
2.
Lee, Yejin, Douglas Barker, Kevin Correia, et al.. (2021). Mutations causing Lopes-Maciel-Rodan syndrome are huntingtin hypomorphs. Human Molecular Genetics. 30(3-4). 135–148. 20 indexed citations
3.
Loupe, Jacob M., Ricardo Mouro Pinto, Kyung‐Hee Kim, et al.. (2020). Promotion of somatic CAG repeat expansion by Fan1 knock-out in Huntington’s disease knock-in mice is blocked by Mlh1 knock-out. Human Molecular Genetics. 29(18). 3044–3053. 50 indexed citations
4.
Kovalenko, Marina, Austen J. Milnerwood, Jason St. Claire, et al.. (2018). HttQ111/+ Huntington’s Disease Knock-in Mice Exhibit Brain Region-Specific Morphological Changes and Synaptic Dysfunction. Journal of Huntington s Disease. 7(1). 17–33. 25 indexed citations
5.
Hung, Claudia Lin-Kar, Tamara Maiuri, Tammy Gillis, et al.. (2018). A patient-derived cellular model for Huntington’s disease reveals phenotypes at clinically relevant CAG lengths. Molecular Biology of the Cell. 29(23). 2809–2820. 21 indexed citations
6.
Long, Jeffrey D., Jong‐Min Lee, Elizabeth Aylward, et al.. (2018). Genetic Modification of Huntington Disease Acts Early in the Prediagnosis Phase. The American Journal of Human Genetics. 103(3). 349–357. 22 indexed citations
7.
Chao, Michael J., Tammy Gillis, Ranjit Singh Atwal, et al.. (2017). Haplotype-based stratification of Huntington's disease. European Journal of Human Genetics. 25(11). 1202–1209. 18 indexed citations
8.
Shin, Aram, Jun Wan Shin, Kyung‐Hee Kim, et al.. (2017). Novel allele-specific quantification methods reveal no effects of adult onset CAG repeats on HTT mRNA and protein levels. Human Molecular Genetics. 26(7). 1258–1267. 14 indexed citations
9.
Rodan, Lance H., Julie S. Cohen, Ali Fatemi, et al.. (2016). A novel neurodevelopmental disorder associated with compound heterozygous variants in the huntingtin gene. European Journal of Human Genetics. 24(12). 1826–1827. 45 indexed citations
10.
Shin, Aram, Tammy Gillis, Jayalakshmi Srinidhi Mysore, et al.. (2016). The HTT CAG-Expansion Mutation Determines Age at Death but Not Disease Duration in Huntington Disease. The American Journal of Human Genetics. 98(2). 287–298. 103 indexed citations
11.
Lee, Jong‐Min, Kyung‐Hee Kim, Aram Shin, et al.. (2015). Sequence-Level Analysis of the Major European Huntington Disease Haplotype. The American Journal of Human Genetics. 97(3). 435–444. 17 indexed citations
12.
Ramos, Eliana Marisa, Marina Kovalenko, Jolene R. Guide, et al.. (2015). Chromosome substitution strain assessment of a Huntington’s disease modifier locus. Mammalian Genome. 26(3-4). 119–130. 3 indexed citations
13.
Lee, Jong‐Min, Rachel Levantovsky, Elisa Fossale, et al.. (2013). Dominant effects of the Huntington's disease HTT CAG repeat length are captured in gene-expression data sets by a continuous analysis mathematical modeling strategy. Human Molecular Genetics. 22(16). 3227–3238. 21 indexed citations
14.
Kovalenko, Marina, Ella Dragileva, Jason St. Claire, et al.. (2012). Msh2 Acts in Medium-Spiny Striatal Neurons as an Enhancer of CAG Instability and Mutant Huntingtin Phenotypes in Huntington’s Disease Knock-In Mice. PLoS ONE. 7(9). e44273–e44273. 59 indexed citations
15.
16.
Lee, Jong‐Min, Jie Zhang, Andrew I. Su, et al.. (2010). A novel approach to investigate tissue-specific trinucleotide repeat instability. BMC Systems Biology. 4(1). 29–29. 84 indexed citations
17.
Kishikawa, Shotaro, Jian‐Liang Li, Tammy Gillis, et al.. (2006). Brain-derived neurotrophic factor does not influence age at neurologic onset of Huntington’s disease. Neurobiology of Disease. 24(2). 280–285. 27 indexed citations
18.
Lloret, Alejandro, Ella Dragileva, Janice A. Espinola, et al.. (2006). Genetic background modifies nuclear mutant huntingtin accumulation and HD CAG repeat instability in Huntington's disease knock-in mice. Human Molecular Genetics. 15(12). 2015–2024. 68 indexed citations
19.
Zeng, Wenqi, Tammy Gillis, Luc Djoussé, et al.. (2006). Genetic analysis of the GRIK2modifier effect in Huntington's disease. BMC Neuroscience. 7(1). 62–62. 16 indexed citations
20.
Gao, Hanlin, Rose-Mary N. Boustany, Janice A. Espinola, et al.. (2002). Mutations in a Novel CLN6-Encoded Transmembrane Protein Cause Variant Neuronal Ceroid Lipofuscinosis in Man and Mouse. The American Journal of Human Genetics. 70(2). 324–335. 167 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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