Michail Yekelchyk

634 total citations
9 papers, 367 citations indexed

About

Michail Yekelchyk is a scholar working on Molecular Biology, Cancer Research and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Michail Yekelchyk has authored 9 papers receiving a total of 367 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Michail Yekelchyk's work include Congenital heart defects research (4 papers), Single-cell and spatial transcriptomics (3 papers) and Cardiac Fibrosis and Remodeling (2 papers). Michail Yekelchyk is often cited by papers focused on Congenital heart defects research (4 papers), Single-cell and spatial transcriptomics (3 papers) and Cardiac Fibrosis and Remodeling (2 papers). Michail Yekelchyk collaborates with scholars based in Germany, Portugal and United States. Michail Yekelchyk's co-authors include Jens Preussner, Stefan Günther, Thomas Braun, Mario Looso, Yonggang Zhou, Xi Chen, Xuejun Yuan, Guangshuai Jia, Sarah A. Teichmann and Carsten Kuenne and has published in prestigious journals such as Circulation, Nature Communications and The EMBO Journal.

In The Last Decade

Michail Yekelchyk

6 papers receiving 367 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michail Yekelchyk Germany	6	276	84	53	48	40	9	367
Anne-Claire Godet France	7	257 0.9×	117 1.4×	50 0.9×	25 0.5×	85 2.1×	9	374
Yun Deng China	13	236 0.9×	46 0.5×	32 0.6×	28 0.6×	28 0.7×	26	323
Christos Tzimas United States	10	157 0.6×	66 0.8×	52 1.0×	73 1.5×	45 1.1×	13	298
Annamarie C. Dalton United States	10	282 1.0×	55 0.7×	24 0.5×	60 1.3×	94 2.4×	13	381
Daniel E. Foxler United Kingdom	8	203 0.7×	113 1.3×	15 0.3×	26 0.5×	38 0.9×	9	286
Zheng Meng United States	13	323 1.2×	105 1.3×	23 0.4×	35 0.7×	37 0.9×	21	403
Laura C. Cobbold United Kingdom	7	404 1.5×	69 0.8×	81 1.5×	21 0.4×	41 1.0×	7	453
Alessandra Vigilante United Kingdom	8	378 1.4×	83 1.0×	14 0.3×	33 0.7×	56 1.4×	16	463
Xiao Albert Zhou China	8	366 1.3×	242 2.9×	22 0.4×	59 1.2×	82 2.0×	14	512
Shaikamjad Umesalma United States	8	206 0.7×	99 1.2×	21 0.4×	21 0.4×	66 1.6×	10	319

Countries citing papers authored by Michail Yekelchyk

Since Specialization

Citations

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

Fields of papers citing papers by Michail Yekelchyk

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michail Yekelchyk

This figure shows the co-authorship network connecting the top 25 collaborators of Michail Yekelchyk. A scholar is included among the top collaborators of Michail Yekelchyk 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 Michail Yekelchyk. Michail Yekelchyk 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

Cardeira-da-Silva, João, Stefan Günther, Radhan Ramadass, et al.. (2024). Antigen presentation plays positive roles in the regenerative response to cardiac injury in zebrafish. Nature Communications. 15(1). 3637–3637. 9 indexed citations

Wagner, Julian U. G., Lukas Tombor, Simone-Franziska Glaser, et al.. (2024). Abstract 4143675: The epigenetically regulated transcription factor ZBTB16 protects against cardiac aging. Circulation. 150(Suppl_1).

Yekelchyk, Michail, Xiang Li, Stefan Günther, & Thomas Braun. (2024). Single-Nucleus ATAC-seq for Mapping Chromatin Accessibility in Individual Cells of Murine Hearts. Methods in molecular biology. 2752. 245–257.

Parker, Taylor M., Kartik Gupta, Antonio Palma, et al.. (2021). Cell competition in intratumoral and tumor microenvironment interactions. The EMBO Journal. 40(17). e107271–e107271. 62 indexed citations

Yekelchyk, Michail & Thomas Braun. (2021). Mono- and Multi-nucleated Cardiomyocytes Do Not Constitute Transcriptionally Distinct Entities. 2(1).

Madan, Esha, Peter Dimitrion, Timothy D. Eubank, et al.. (2020). Cell Competition Boosts Clonal Evolution and Hypoxic Selection in Cancer. Trends in Cell Biology. 30(12). 967–978. 19 indexed citations

Yekelchyk, Michail, Stefan Günther, Jens Preussner, & Thomas Braun. (2019). Mono- and multi-nucleated ventricular cardiomyocytes constitute a transcriptionally homogenous cell population. Basic Research in Cardiology. 114(5). 36–36. 65 indexed citations

Leisegang, Matthias S., Sofia‐Iris Bibli, Stefan Günther, et al.. (2019). Pleiotropic effects of laminar flow and statins depend on the Krüppel-like factor-induced lncRNA MANTIS. European Heart Journal. 40(30). 2523–2533. 56 indexed citations

Jia, Guangshuai, Jens Preussner, Xi Chen, et al.. (2018). Single cell RNA-seq and ATAC-seq analysis of cardiac progenitor cell transition states and lineage settlement. Nature Communications. 9(1). 4877–4877. 156 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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