Matthew Tudor

4.6k citations
35 papers · 3.5k indexed · 2 hit papers · h-index 20
Topics
Computational Drug Discovery Methods (9 papers)Machine Learning in Materials Science (5 papers)Plant Reproductive Biology (4 papers)

In The Last Decade

Matthew Tudor

34 papers receiving 3.4k citations

Hit Papers

Deficiency of methyl-CpG binding protein-2 in CNS neurons...2001202620092017200120012505007501000

Peers

Matthew Tudor
Comparison fields: 5 of 127
  • Molecular Biology 2.5k
  • Genetics 1.5k
  • Cognitive Neuroscience 638
  • Plant Science 623
  • Computational Theory and Mathematics 268
Replace Scott Dewell with:
Scott Dewell United States
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Aaron K. Wong United States
Mark O. Collins United Kingdom
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Matthew Tudor relative to Scott Dewell United States Scott Dewell's profile →
Citations per field
00.5×7.7×
Scott Dewell · 1×
Citations per year

Countries citing papers authored by Matthew Tudor

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Tudor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Tudor

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Tudor. A scholar is included among the top collaborators of Matthew Tudor 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 Tudor. Matthew Tudor 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
#WorkIndexed citations
1 0
2 1
3 15
4 7
5 43
6 188
7 3
8
Chapter Five - High-Throughput Screening
3
9 10
10 96
11 53
12 12
13 58
14 18
15 6
16
Loss of genomic methylation causes p53-dependent apoptosis and epigenetic deregulationbreakdown →
559
17 30
18 163
19 172
20 109

About Matthew Tudor

Matthew Tudor is a scholar working on Computational Theory and Mathematics, Molecular Biology and Biophysics, having authored 35 papers that have together received 3.5k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Machine Learning in Materials Science (5 papers) and Plant Reproductive Biology (4 papers). The work is most often cited by research in Genetics (1.5k citations), Molecular Biology (2.5k citations) and Cognitive Neuroscience (638 citations). Matthew Tudor has collaborated with scholars based in United States, Switzerland and Czechia. Frequent co-authors include Rudolf Jaenisch, Richard Z. Chen, Schahram Akbarian, Hong Mā, Yi Hu, Sara Cherry, Eric S. Lander, Christopher Wilson, Peggy Lee and Györgyi Csankovszki. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Genetics and Genes & Development.

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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