Eric Lader

1.9k total citations
21 papers, 906 citations indexed

About

Eric Lader is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Eric Lader has authored 21 papers receiving a total of 906 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 7 papers in Cancer Research and 6 papers in Genetics. Recurrent topics in Eric Lader's work include Molecular Biology Techniques and Applications (4 papers), RNA Interference and Gene Delivery (4 papers) and Reproductive Biology and Fertility (3 papers). Eric Lader is often cited by papers focused on Molecular Biology Techniques and Applications (4 papers), RNA Interference and Gene Delivery (4 papers) and Reproductive Biology and Fertility (3 papers). Eric Lader collaborates with scholars based in United States, Germany and United Kingdom. Eric Lader's co-authors include Jonathan M. Shaffer, Markus Sprenger‐Haussels, Mikkel Noerholm, Emily G. Berghoff, Johan Skog, Daniel Enderle, Alexandra Spiel, Christine M. Coticchia, Romy Mueller and Martin Schlumpberger and has published in prestigious journals such as Cell, Nucleic Acids Research and PLoS ONE.

In The Last Decade

Eric Lader

21 papers receiving 890 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric Lader United States 14 600 303 138 129 94 21 906
Hyo‐Sung Jeon South Korea 20 775 1.3× 395 1.3× 83 0.6× 65 0.5× 57 0.6× 37 1.1k
A. Robins United Kingdom 17 231 0.4× 111 0.4× 48 0.3× 114 0.9× 74 0.8× 24 725
Haukeline H. Volders Netherlands 16 475 0.8× 178 0.6× 379 2.7× 213 1.7× 273 2.9× 19 1.1k
Claire E. Senner United Kingdom 21 1.2k 1.9× 142 0.5× 295 2.1× 235 1.8× 252 2.7× 23 1.6k
Wei Jia China 18 459 0.8× 276 0.9× 84 0.6× 34 0.3× 131 1.4× 58 893
Katsuyuki Adachi Japan 18 561 0.9× 163 0.5× 56 0.4× 62 0.5× 245 2.6× 39 1.2k
Angela Grassi Italy 13 400 0.7× 293 1.0× 37 0.3× 22 0.2× 86 0.9× 27 707
Paul Mellor United Kingdom 20 478 0.8× 131 0.4× 31 0.2× 69 0.5× 57 0.6× 32 1.1k
Surya Pavan Yenamandra Sweden 17 448 0.7× 192 0.6× 108 0.8× 63 0.5× 76 0.8× 21 760
J. Bradford Kline United States 17 379 0.6× 73 0.2× 109 0.8× 120 0.9× 72 0.8× 29 1.1k

Countries citing papers authored by Eric Lader

Since Specialization
Citations

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

Fields of papers citing papers by Eric Lader

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Lader

This figure shows the co-authorship network connecting the top 25 collaborators of Eric Lader. A scholar is included among the top collaborators of Eric Lader 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 Eric Lader. Eric Lader 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.
Storbeck, Markus, et al.. (2023). Optimized Workflow for Whole Genome and Transcriptome Next‐Generation Sequencing of Single Cells or Limited Nucleic Acid Samples. Current Protocols. 3(5). e753–e753. 2 indexed citations
2.
Darwanto, Agus, Anne-Mette K. Hein, Sascha Strauß, et al.. (2017). Use of the QIAGEN GeneReader NGS system for detection of KRAS mutations, validated by the QIAGEN Therascreen PCR kit and alternative NGS platform. BMC Cancer. 17(1). 358–358. 14 indexed citations
3.
Maertzdorf, Jeroen, Gayle K. McEwen, January Weiner, et al.. (2015). Concise gene signature for point‐of‐care classification of tuberculosis. EMBO Molecular Medicine. 8(2). 86–95. 88 indexed citations
4.
Enderle, Daniel, Alexandra Spiel, Christine M. Coticchia, et al.. (2015). Characterization of RNA from Exosomes and Other Extracellular Vesicles Isolated by a Novel Spin Column-Based Method. PLoS ONE. 10(8). e0136133–e0136133. 305 indexed citations
5.
Vliegenthart, A. D. Bastiaan, Jonathan M. Shaffer, Joanna I. Clarke, et al.. (2015). Comprehensive microRNA profiling in acetaminophen toxicity identifies novel circulating biomarkers for human liver and kidney injury. Scientific Reports. 5(1). 15501–15501. 102 indexed citations
6.
Tian, Song, Samuel Rulli, & Eric Lader. (2015). Serum lncRNA Detection as Potential Biomarker of Lung Cancer. The FASEB Journal. 29(S1). 2 indexed citations
7.
Köstler, Wolfgang J., Amit Zeisel, Cindy Körner, et al.. (2013). Epidermal Growth-Factor – Induced Transcript Isoform Variation Drives Mammary Cell Migration. PLoS ONE. 8(12). e80566–e80566. 14 indexed citations
8.
Kreutz, Martin, et al.. (2012). Integrated expression profiling of multiple RNA species by real-time PCR. Methods. 59(1). S7–S10. 1 indexed citations
9.
Cabarcas‐Petroski, Stephanie, Suneetha B. Thomas, Xiaohu Zhang, et al.. (2011). The role of upregulated miRNAs and the identification of novel mRNA targets in prostatospheres. Genomics. 99(2). 108–117. 6 indexed citations
10.
Bergauer, Tobias, et al.. (2009). Analysis of Putative miRNA Binding Sites and mRNA 3′ Ends as Targets for siRNA-Mediated Gene Knockdown. Oligonucleotides. 19(1). 41–52. 11 indexed citations
11.
Martin, Scott E., Tamara L. Jones, Cheryl L. Thomas, et al.. (2007). Multiplexing siRNAs to compress RNAi-based screen size in human cells. Nucleic Acids Research. 35(8). e57–e57. 22 indexed citations
12.
Zheng, Bo‐Jian, Yi Guan, Qingquan Tang, et al.. (2004). Prophylactic and Therapeutic Effects of Small Interfering Rna Targeting Sars-Coronavirus. Antiviral Therapy. 9(3). 365–374. 75 indexed citations
13.
Rennebeck, Gabriela, Eric Lader, Atsushi Fujimoto, Elissa P. Lei, & Karen Artzt. (1998). Mouse Brachyury the Second (T2) Is a Gene Next to Classical T and a Candidate Gene for tct. Genetics. 150(3). 1125–1131. 13 indexed citations
14.
Rennebeck, Gabriela, Eric Lader, Qi Chen, et al.. (1995). Is There aBrachyury the Second?Analysis of a Transgenic Mutation Involved in Notochord Maintenance in Mice. Developmental Biology. 172(1). 206–217. 15 indexed citations
15.
Millar, Sarah E., Eric Lader, & Jurrien Dean. (1993). ZAP-1 DNA Binding Activity Is First Detected at the Onset of Zona Pellucida Gene Expression in Embryonic Mouse Oocytes. Developmental Biology. 158(2). 410–413. 31 indexed citations
16.
Lader, Eric, Karen Artzt, & Kenneth W. Adolph. (1993). Polymerase chain reaction from preimplantation mouse embryos: expression studies and genotype analysis.. 358–373. 1 indexed citations
17.
Millar, Sarah E., Eric Lader, Lifang Liang, & Jurrien Dean. (1991). Oocyte-Specific Factors Bind a Conserved Upstream Sequence Required for Mouse Zona Pellucida Promoter Activity. Molecular and Cellular Biology. 11(12). 6197–6204. 5 indexed citations
18.
Millar, Sarah E., Eric Lader, Lifang Liang, & Jurrien Dean. (1991). Oocyte-specific factors bind a conserved upstream sequence required for mouse zona pellucida promoter activity.. Molecular and Cellular Biology. 11(12). 6197–6204. 59 indexed citations
19.
Lader, Eric, et al.. (1989). tctex-1: A candidate gene family for a mouse t complex sterility locus. Cell. 58(5). 969–979. 86 indexed citations
20.

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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