Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
200534.0k citationsVamsi K. Mootha, Eric S. Lander et al.Proceedings of the National Academy of Sciencesprofile →
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression Monitoring
19998.0k citationsEric S. Lander et al.Scienceprofile →
MAPMAKER: An interactive computer package for constructing primary genetic linkage maps of experimental and natural populations
19876.0k citationsEric S. Lander, Mark J. Daly et al.profile →
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
20095.7k citationsErez Lieberman-Aiden, Nynke L. van Berkum et al.Scienceprofile →
The Structure of Haplotype Blocks in the Human Genome
20024.5k citationsEric S. Lander, Mark J. Daly et al.Scienceprofile →
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
20144.4k citationsSuhas S.P. Rao, Miriam Huntley et al.profile →
Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results
Countries citing papers authored by Eric S. Lander
Since
Specialization
Citations
This map shows the geographic impact of Eric S. Lander'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 S. Lander with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric S. Lander more than expected).
This network shows the impact of papers produced by Eric S. Lander. 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 S. Lander. The network helps show where Eric S. Lander may publish in the future.
Co-authorship network of co-authors of Eric S. Lander
This figure shows the co-authorship network connecting the top 25 collaborators of Eric S. Lander.
A scholar is included among the top collaborators of Eric S. Lander 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 S. Lander. Eric S. Lander is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lander, Eric S., Françoise Βaylis, Feng Zhang, et al.. (2019). Adopt a moratorium on heritable genome editing. Nature. 567(7747). 165–168.251 indexed citations breakdown →
3.
Durand, Neva C., Muhammad S. Shamim, Ido Machol, et al.. (2016). Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments. Cell Systems. 3(1). 95–98.2026 indexed citations breakdown →
Fulco, Charles P., Mathias Munschauer, Rockwell Anyoha, et al.. (2016). Systematic mapping of functional enhancer–promoter connections with CRISPR interference. Science. 354(6313). 769–773.390 indexed citations breakdown →
6.
Abudayyeh, Omar O., Jonathan S. Gootenberg, Silvana Konermann, et al.. (2016). C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector. Science. 353(6299). aaf5573–aaf5573.1689 indexed citations breakdown →
7.
Wang, Timothy C., Kıvanç Birsoy, Nicholas W. Hughes, et al.. (2015). Identification and characterization of essential genes in the human genome. Science. 350(6264). 1096–1101.1075 indexed citations breakdown →
8.
Lander, Eric S.. (2014). Whole-exome sequencing and clinical interpretation of FFPE tumor samples to guide precision cancer medicine. DSpace@MIT (Massachusetts Institute of Technology).2 indexed citations
Zuk, Or, Eliana Hechter, Shamil Sunyaev, & Eric S. Lander. (2012). The mystery of missing heritability: Genetic interactions create phantom heritability. Proceedings of the National Academy of Sciences. 109(4). 1193–1198.1007 indexed citations breakdown →
11.
Gnerre, Sante, Iain MacCallum, Dariusz Przybylski, et al.. (2010). High-quality draft assemblies of mammalian genomes from massively parallel sequence data. Proceedings of the National Academy of Sciences. 108(4). 1513–1518.1037 indexed citations breakdown →
12.
Lieberman-Aiden, Erez, Nynke L. van Berkum, Louise Williams, et al.. (2009). Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome. Science. 326(5950). 289–293.5700 indexed citations breakdown →
13.
Khalil, Ahmad M., Mitchell Guttman, Maite Huarte, et al.. (2009). Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proceedings of the National Academy of Sciences. 106(28). 11667–11672.2331 indexed citations breakdown →
14.
Önder, Tamer T., Piyush B. Gupta, Sendurai A. Mani, et al.. (2008). Loss of E-Cadherin Promotes Metastasis via Multiple Downstream Transcriptional Pathways. Cancer Research. 68(10). 3645–3654.1221 indexed citations breakdown →
Huang, Qian, Dongyu Liu, Joshua M. Korn, et al.. (2001). The Plasticity of Dendritic Cell Responses to Pathogens and Their Components. Science. 294(5543). 870–875.592 indexed citations breakdown →
20.
Hegi, Monika E., Theodora R. Devereux, William F. Dietrich, et al.. (1994). Allelotype analysis of mouse lung carcinomas reveals frequent allelic losses on chromosome 4 and an association between allelic imbalances on chromosome 6 and K-ras activation.. PubMed. 54(23). 6257–64.86 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.