Matthew J. Lyst

1.4k total citations
9 papers, 945 citations indexed

About

Matthew J. Lyst is a scholar working on Molecular Biology, Genetics and Cognitive Neuroscience. According to data from OpenAlex, Matthew J. Lyst has authored 9 papers receiving a total of 945 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Genetics and 3 papers in Cognitive Neuroscience. Recurrent topics in Matthew J. Lyst's work include Genetics and Neurodevelopmental Disorders (8 papers), Ubiquitin and proteasome pathways (5 papers) and Chromatin Remodeling and Cancer (3 papers). Matthew J. Lyst is often cited by papers focused on Genetics and Neurodevelopmental Disorders (8 papers), Ubiquitin and proteasome pathways (5 papers) and Chromatin Remodeling and Cancer (3 papers). Matthew J. Lyst collaborates with scholars based in United Kingdom, United States and Poland. Matthew J. Lyst's co-authors include Adrian Bird, Irina Stancheva, Robert Ekiert, Nathaniel D. Robinson, Daniel H. Ebert, Michael E. Greenberg, Nathaniel R. Kastan, Jim Selfridge, Jacky Guy and Cara Merusi and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Genes & Development.

In The Last Decade

Matthew J. Lyst

9 papers receiving 941 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew J. Lyst United Kingdom	8	722	718	315	53	47	9	945
Nathaniel R. Kastan United States	7	644 0.9×	804 1.1×	270 0.9×	72 1.4×	129 2.7×	7	1.0k
Cara Merusi United Kingdom	10	586 0.8×	753 1.0×	270 0.9×	30 0.6×	24 0.5×	10	915
John B. Vincent Canada	11	878 1.2×	656 0.9×	539 1.7×	113 2.1×	85 1.8×	19	1.1k
Anna Bergo Italy	11	532 0.7×	453 0.6×	158 0.5×	39 0.7×	92 2.0×	11	653
Anthony Leotta United States	6	611 0.8×	426 0.6×	490 1.6×	37 0.7×	13 0.3×	8	907
Astrid Oudakker Netherlands	14	673 0.9×	667 0.9×	177 0.6×	100 1.9×	38 0.8×	20	1.1k
Showming Kwok United States	8	451 0.6×	615 0.9×	227 0.7×	103 1.9×	36 0.8×	9	827
Kamal K.E. Gadalla United Kingdom	9	390 0.5×	366 0.5×	206 0.7×	39 0.7×	42 0.9×	14	566
Zhou Xp China	5	306 0.4×	416 0.6×	227 0.7×	47 0.9×	34 0.7×	8	634
Hélène Cheval France	7	492 0.7×	428 0.6×	284 0.9×	79 1.5×	27 0.6×	9	673

Countries citing papers authored by Matthew J. Lyst

Since Specialization

Citations

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

Fields of papers citing papers by Matthew J. Lyst

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew J. Lyst. 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 Matthew J. Lyst. The network helps show where Matthew J. Lyst may publish in the future.

Co-authorship network of co-authors of Matthew J. Lyst

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew J. Lyst. A scholar is included among the top collaborators of Matthew J. Lyst 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 Matthew J. Lyst. Matthew J. Lyst is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Zhang, Li, Almer M. van der Sloot, Sylvain Tollis, et al.. (2023). A screen for MeCP2-TBL1 interaction inhibitors using a luminescence-based assay. Scientific Reports. 13(1). 3868–3868. 1 indexed citations

2.

Tillotson, Rebekah, Justyna Cholewa-Waclaw, John Connelly, et al.. (2021). Neuronal non-CG methylation is an essential target for MeCP2 function. Molecular Cell. 81(6). 1260–1275.e12. 29 indexed citations

3.

Lyst, Matthew J., Robert Ekiert, Jacky Guy, et al.. (2018). Affinity for DNA Contributes to NLS Independent Nuclear Localization of MeCP2. Cell Reports. 24(9). 2213–2220. 30 indexed citations

4.

Koerner, Martha V., Jim Selfridge, Jacky Guy, et al.. (2018). Toxicity of overexpressed MeCP2 is independent of HDAC3 activity. Genes & Development. 32(23-24). 1514–1524. 24 indexed citations

5.

Lyst, Matthew J., et al.. (2017). Structure of the MeCP2–TBLR1 complex reveals a molecular basis for Rett syndrome and related disorders. Proceedings of the National Academy of Sciences. 114(16). E3243–E3250. 61 indexed citations

6.

Lyst, Matthew J. & Adrian Bird. (2015). Rett syndrome: a complex disorder with simple roots. Nature Reviews Genetics. 16(5). 261–275. 257 indexed citations

7.

Ebert, Daniel H., Harrison W. Gabel, Nathaniel D. Robinson, et al.. (2013). Activity-dependent phosphorylation of MeCP2 threonine 308 regulates interaction with NCoR. Nature. 499(7458). 341–345. 167 indexed citations

8.

Lyst, Matthew J., Robert Ekiert, Daniel H. Ebert, et al.. (2013). Rett syndrome mutations abolish the interaction of MeCP2 with the NCoR/SMRT co-repressor. Nature Neuroscience. 16(7). 898–902. 288 indexed citations

9.

Lyst, Matthew J. & Irina Stancheva. (2007). A role for SUMO modification in transcriptional repression and activation. Biochemical Society Transactions. 35(6). 1389–1392. 88 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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