Dmitry Svetlichnyy

2.5k citations
7 papers · 1.6k indexed · 3 hit papers · h-index 7
Topics
Genomics and Chromatin Dynamics (4 papers)RNA Research and Splicing (2 papers)Gene expression and cancer classification (1 paper)

In The Last Decade

Dmitry Svetlichnyy

7 papers receiving 1.6k citations

Hit Papers

iRegulon: From a Gene List to a Gene Regulatory Network U...2014202620182022201420182020200400600

Peers

Dmitry Svetlichnyy
Comparison fields: 5 of 159
  • Molecular Biology 908
  • Immunology 383
  • Oncology 295
  • Cancer Research 217
  • Cell Biology 138
Replace Gianni Monaco with:
Gianni Monaco Italy
Kevin J. Whitehead United States
Flavia Frabetti Italy
Timothy I. Shaw United States
David Huss United States
Rene Sit United States
Mario Looso Germany
Toshiya Sato Japan
Amy Chen United States
Yue Shi China
Dmitry Svetlichnyy relative to Gianni Monaco Italy Gianni Monaco's profile →
Citations per field
00.5×5.2×
Gianni Monaco · 1×
Citations per year

Countries citing papers authored by Dmitry Svetlichnyy

Since Specialization
Citations

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

Fields of papers citing papers by Dmitry Svetlichnyy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dmitry Svetlichnyy

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

All Works

7 of 7 papers shown
#WorkIndexed citations
1
Coupled scRNA-Seq and Intracellular Protein Activity Reveal an Immunosuppressive Role of TREM2 in Cancerbreakdown →
309
2
ACE-inhibition induces a cardioprotective transcriptional response in the metabolic syndrome heartbreakdown →
356
3 11
4 62
5 280
6 17
7
iRegulon: From a Gene List to a Gene Regulatory Network Using Large Motif and Track Collectionsbreakdown →
610

About Dmitry Svetlichnyy

Dmitry Svetlichnyy is a scholar working on Neurology, Molecular Biology and Cancer Research, having authored 7 papers that have together received 1.6k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (4 papers), RNA Research and Splicing (2 papers) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Immunology (383 citations), Cancer Research (217 citations) and Molecular Biology (908 citations). Dmitry Svetlichnyy has collaborated with scholars based in Belgium, United States and Israel. Frequent co-authors include Stein Aerts, Hana Imrichová, Zeynep Kalender Atak, Mark Fiers, Gert Hulselmans, Valerie Christiaens, Annelien Verfaillie, Jean‐Christophe Marine, Bram Van de Sande and Koen Herten. Their work appears in journals such as Cell, Nature Communications and Scientific Reports.

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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