Shane Neph

33.0k total citations · 2 hit papers
15 papers, 3.2k citations indexed

About

Shane Neph is a scholar working on Molecular Biology, Plant Science and Artificial Intelligence. According to data from OpenAlex, Shane Neph has authored 15 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 4 papers in Plant Science and 2 papers in Artificial Intelligence. Recurrent topics in Shane Neph's work include RNA and protein synthesis mechanisms (8 papers), Genomics and Chromatin Dynamics (7 papers) and Genomics and Phylogenetic Studies (6 papers). Shane Neph is often cited by papers focused on RNA and protein synthesis mechanisms (8 papers), Genomics and Chromatin Dynamics (7 papers) and Genomics and Phylogenetic Studies (6 papers). Shane Neph collaborates with scholars based in United States, Australia and United Kingdom. Shane Neph's co-authors include J Stamatoyannopoulos, Alex Reynolds, Richard Sandstrom, Eric Haugen, Robert E. Thurman, Michael S. Kuehn, Andrew B. Stergachis, Richard Humbert, Jeff Vierstra and Peter J. Sabo and has published in prestigious journals such as Cell, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Shane Neph

15 papers receiving 3.2k citations

Hit Papers

align trajectories

What are hit papers?

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.

BEDOPS: high-performance genomic feature operations

2012 635 citations Shane Neph, Michael S. Kuehn et al. Bioinformatics profile →
The Human Mitochondrial Transcriptome

2011 631 citations Tim R. Mercer, Shane Neph et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shane Neph United States	14	2.6k	548	417	398	316	15	3.2k
Jessica Severin Japan	17	2.0k 0.8×	661 1.2×	247 0.6×	219 0.6×	296 0.9×	25	2.8k
Daniel Ríos United Kingdom	8	1.8k 0.7×	704 1.3×	202 0.5×	313 0.8×	259 0.8×	14	2.9k
Brian T. Wilhelm Canada	26	2.3k 0.9×	263 0.5×	645 1.5×	431 1.1×	302 1.0×	54	3.2k
Jenny M. Kelley United States	11	2.2k 0.9×	646 1.2×	215 0.5×	174 0.4×	478 1.5×	14	3.0k
Yvonne J. K. Edwards United States	26	1.7k 0.7×	566 1.0×	226 0.5×	206 0.5×	288 0.9×	67	2.5k
Sarah Kummerfeld Australia	21	2.2k 0.9×	384 0.7×	429 1.0×	329 0.8×	191 0.6×	40	3.1k
Dario Boffelli United States	29	2.4k 0.9×	647 1.2×	155 0.4×	619 1.6×	409 1.3×	61	3.1k
Matthew N. Bainbridge United States	30	2.4k 0.9×	1.3k 2.4×	228 0.5×	595 1.5×	222 0.7×	62	3.8k
Mônica Beltrame Italy	25	2.1k 0.8×	367 0.7×	314 0.8×	157 0.4×	175 0.6×	48	2.8k
Karyn Meltz Steinberg United States	17	1.3k 0.5×	826 1.5×	210 0.5×	262 0.7×	341 1.1×	22	2.1k

Countries citing papers authored by Shane Neph

Since Specialization

Citations

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

Fields of papers citing papers by Shane Neph

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shane Neph

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

All Works

Sort: Min cites: Since: Top N: Style:

15 of 15 papers shown

Breeze, Charles E., Alex Reynolds, Jenny van Dongen, et al.. (2019). eFORGE v2.0: updated analysis of cell type-specific signal in epigenomic data. Bioinformatics. 35(22). 4767–4769. 60 indexed citations

Sullivan, Alessandra M., Andrej A. Arsovski, Richard Sandstrom, et al.. (2019). Mapping and Dynamics of Regulatory DNA in Maturing Arabidopsis thaliana Siliques. Frontiers in Plant Science. 10. 1434–1434. 14 indexed citations

Neph, Shane, Alex Reynolds, Michael S. Kuehn, & J Stamatoyannopoulos. (2016). Operating on Genomic Ranges Using BEDOPS. Methods in molecular biology. 1418. 267–281. 7 indexed citations

Stergachis, Andrew B., Shane Neph, Alex Reynolds, et al.. (2013). Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes. Cell. 154(4). 888–903. 241 indexed citations

Mercer, Tim R., Stacey L. Edwards, Michael B. Clark, et al.. (2013). DNase I–hypersensitive exons colocalize with promoters and distal regulatory elements. Nature Genetics. 45(8). 852–859. 97 indexed citations

Vernot, Benjamin, Andrew B. Stergachis, Matthew T. Maurano, et al.. (2012). Personal and population genomics of human regulatory variation. Genome Research. 22(9). 1689–1697. 79 indexed citations

Samstein, Robert, Aaron Arvey, Steven Z. Josefowicz, et al.. (2012). Foxp3 Exploits a Pre-Existent Enhancer Landscape for Regulatory T Cell Lineage Specification. Cell. 151(1). 153–166. 356 indexed citations

Neph, Shane, Andrew B. Stergachis, Alex Reynolds, et al.. (2012). Circuitry and Dynamics of Human Transcription Factor Regulatory Networks. Cell. 150(6). 1274–1286. 321 indexed citations

Neph, Shane, Michael S. Kuehn, Alex Reynolds, et al.. (2012). BEDOPS: high-performance genomic feature operations. Bioinformatics. 28(14). 1919–1920. 635 indexed citations breakdown →

10.

Mercer, Tim R., Shane Neph, Marcel E. Dinger, et al.. (2011). The Human Mitochondrial Transcriptome. Cell. 146(4). 645–658. 631 indexed citations breakdown →

11.

Hesselberth, Jay R., Xiaoyu Chen, Zhihong Zhang, et al.. (2009). Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nature Methods. 6(4). 283–289. 429 indexed citations

12.

Attanasio, Catia, Alexandre Reymond, Richard Humbert, et al.. (2008). Assaying the regulatory potential of mammalian conserved non-coding sequences in human cells. Genome biology. 9(12). R168–R168. 16 indexed citations

13.

Weinberg, Zasha, Jeffrey E. Barrick, Zizhen Yao, et al.. (2007). Identification of 22 candidate structured RNAs in bacteria using the CMfinder comparative genomics pipeline. Nucleic Acids Research. 35(14). 4809–4819. 241 indexed citations

14.

Yao, Zizhen, Jeffrey E. Barrick, Zasha Weinberg, et al.. (2007). A Computational Pipeline for High- Throughput Discovery of cis-Regulatory Noncoding RNA in Prokaryotes. PLoS Computational Biology. 3(7). e126–e126. 71 indexed citations

15.

Neph, Shane & Martin Tompa. (2006). MicroFootPrinter: a tool for phylogenetic footprinting in prokaryotic genomes. Nucleic Acids Research. 34(Web Server). W366–W368. 21 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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