Martin Akerman

2.6k total citations · 1 hit paper
22 papers, 1.9k citations indexed

About

Martin Akerman is a scholar working on Molecular Biology, Cancer Research and Immunology and Allergy. According to data from OpenAlex, Martin Akerman has authored 22 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 5 papers in Cancer Research and 2 papers in Immunology and Allergy. Recurrent topics in Martin Akerman's work include RNA Research and Splicing (18 papers), RNA modifications and cancer (17 papers) and RNA and protein synthesis mechanisms (11 papers). Martin Akerman is often cited by papers focused on RNA Research and Splicing (18 papers), RNA modifications and cancer (17 papers) and RNA and protein synthesis mechanisms (11 papers). Martin Akerman collaborates with scholars based in United States, Israel and Denmark. Martin Akerman's co-authors include Adrian R. Krainer, Shipra Das, Olga Anczuków, Adrian R. Krainer, Rotem Karni, Senthil K. Muthuswamy, Lixing Zhan, Avi Z. Rosenberg, Gayatri Arun and Yael Mandel‐Gutfreund and has published in prestigious journals such as Nucleic Acids Research, Journal of Clinical Oncology and Genes & Development.

In The Last Decade

Martin Akerman

21 papers receiving 1.9k citations

Hit Papers

Differentiation of mammary tumors and reduction in metast... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Akerman United States 16 1.7k 743 99 91 62 22 1.9k
Johanna C. Scheuermann Germany 8 1.4k 0.8× 731 1.0× 65 0.7× 112 1.2× 52 0.8× 8 1.6k
Ivana De Martino Italy 10 1.3k 0.7× 1.1k 1.5× 107 1.1× 151 1.7× 42 0.7× 12 1.6k
Ruiyun Xing China 9 1.5k 0.9× 1.3k 1.7× 103 1.0× 112 1.2× 42 0.7× 14 1.8k
Virginie Olive United States 11 1.1k 0.7× 1.1k 1.4× 219 2.2× 120 1.3× 38 0.6× 12 1.5k
Nadya Dimitrova United States 15 1.6k 0.9× 784 1.1× 82 0.8× 267 2.9× 36 0.6× 20 1.8k
Marcel Köhn Germany 12 1.2k 0.7× 675 0.9× 61 0.6× 91 1.0× 23 0.4× 20 1.3k
Nadine Bley Germany 16 1.2k 0.7× 791 1.1× 58 0.6× 97 1.1× 22 0.4× 20 1.4k
Mayuko Furuta Japan 9 980 0.6× 901 1.2× 54 0.5× 99 1.1× 19 0.3× 13 1.2k
Martin Hart Germany 22 879 0.5× 745 1.0× 214 2.2× 101 1.1× 23 0.4× 43 1.2k
M Bennett United States 9 811 0.5× 643 0.9× 211 2.1× 112 1.2× 36 0.6× 9 1.1k

Countries citing papers authored by Martin Akerman

Since Specialization
Citations

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

Fields of papers citing papers by Martin Akerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Akerman

This figure shows the co-authorship network connecting the top 25 collaborators of Martin Akerman. A scholar is included among the top collaborators of Martin Akerman 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 Martin Akerman. Martin Akerman 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.
Manzanares, Miguel, et al.. (2024). Development and validation of AI/ML derived splice-switching oligonucleotides. Molecular Systems Biology. 20(6). 676–701. 4 indexed citations
4.
Dhingra, Priyanka, et al.. (2021). Abstract P170: SpliceCore® a platform for identifying aberrant alternative splicing in triple negative breast cancer for novel therapeutic development. Molecular Cancer Therapeutics. 20(12_Supplement). P170–P170. 1 indexed citations
5.
Park, Sung‐Hee, Mattia Brugiolo, Martin Akerman, et al.. (2019). Differential Functions of Splicing Factors in Mammary Transformation and Breast Cancer Metastasis. Cell Reports. 29(9). 2672–2688.e7. 71 indexed citations
6.
Lei, Sheng, Bo Wan, Junjie Sun, et al.. (2017). Downregulation of Survivin contributes to cell-cycle arrest during postnatal cardiac development in a severe spinal muscular atrophy mouse model. Human Molecular Genetics. 27(3). 486–498. 30 indexed citations
7.
Arun, Gayatri, Sarah D. Diermeier, Martin Akerman, et al.. (2016). Abstract PR11: Differentiation of mammary tumors and reduction in metastasis upon Malat1 LncRNA loss. Cancer Research. 76(6_Supplement). PR11–PR11. 6 indexed citations
8.
Anczuków, Olga, Martin Akerman, Antoine Cléry, et al.. (2015). SRSF1-Regulated Alternative Splicing in Breast Cancer. Molecular Cell. 60(1). 105–117. 244 indexed citations
9.
Arun, Gayatri, Sarah D. Diermeier, Martin Akerman, et al.. (2015). Differentiation of mammary tumors and reduction in metastasis upon Malat1 lncRNA loss. Genes & Development. 30(1). 34–51. 468 indexed citations breakdown →
10.
Akerman, Martin, Oliver I. Fregoso, Shipra Das, et al.. (2015). Differential connectivity of splicing activators and repressors to the human spliceosome. Genome Biology. 16(1). 119–119. 34 indexed citations
11.
Fregoso, Oliver I., Shipra Das, Martin Akerman, & Adrian R. Krainer. (2013). Splicing-Factor Oncoprotein SRSF1 Stabilizes p53 via RPL5 and Induces Cellular Senescence. Molecular Cell. 50(1). 56–66. 92 indexed citations
12.
Roca, Xavier, Martin Akerman, Hans Gaus, et al.. (2012). Widespread recognition of 5′ splice sites by noncanonical base-pairing to U1 snRNA involving bulged nucleotides. Genes & Development. 26(10). 1098–1109. 74 indexed citations
13.
Anczuków, Olga, Avi Z. Rosenberg, Martin Akerman, et al.. (2012). The splicing factor SRSF1 regulates apoptosis and proliferation to promote mammary epithelial cell transformation. Nature Structural & Molecular Biology. 19(2). 220–228. 330 indexed citations
14.
Das, Shipra, Olga Anczuków, Martin Akerman, & Adrian R. Krainer. (2012). Oncogenic Splicing Factor SRSF1 Is a Critical Transcriptional Target of MYC. Cell Reports. 1(2). 110–117. 158 indexed citations
15.
Wang, Zhenxun, Hyun Yong Jeon, Martin Akerman, et al.. (2011). Exon-centric regulation of pyruvate kinase M alternative splicing via mutually exclusive exons. Journal of Molecular Cell Biology. 4(2). 79–87. 87 indexed citations
16.
Akerman, Martin, et al.. (2010). SFmap: a web server for motif analysis and prediction of splicing factor binding sites. Nucleic Acids Research. 38(Web Server). W281–W285. 82 indexed citations
17.
Thorsen, Kasper, Francisco Mansilla, Troels Schepeler, et al.. (2010). Alternative Splicing of SLC39A14 in Colorectal Cancer is Regulated by the Wnt Pathway. Molecular & Cellular Proteomics. 10(1). M110.002998–M110.002998. 77 indexed citations
18.
Akerman, Martin, et al.. (2009). A computational approach for genome-wide mapping of splicing factor binding sites. Genome biology. 10(3). R30–R30. 52 indexed citations
19.
Akerman, Martin & Yael Mandel‐Gutfreund. (2007). Does distance matter? Variations in alternative 3′ splicing regulation. Nucleic Acids Research. 35(16). 5487–5498. 16 indexed citations
20.
Akerman, Martin. (2006). Alternative splicing regulation at tandem 3' splice sites. Nucleic Acids Research. 34(1). 23–31. 63 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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