Jeff Nie

13.0k citations
20 papers · 9.4k indexed · 2 hit papers · h-index 17

Jeff Nie

20 papers receiving 9.2k citations

Hit Papers

Whole-Genome Analysis of Histone H3 Lysine 4 and Lysine 2...54420072026201320192.5k5.0k7.5k

Peers

Jeff Nie
Comparison fields: 5 of 147
  • Molecular Biology 8.3k
  • Developmental Neuroscience 389
  • Genetics 810
  • Aging 110
  • Cellular and Molecular Neuroscience 772
Replace Guðrún A. Jónsdóttir with:
Guðrún A. Jónsdóttir United States
Kim Smuga-Otto United States
Maxim A. Vodyanik United States
In-Hyun Park United States
Shulan Tian United States
William E. Lowry United States
Matthias Stadtfeld United States
Andrew G. Elefanty Australia
Majlinda Lako United Kingdom
Christopher J. Lengner United States
Jeff Nie relative to Guðrún A. Jónsdóttir United States Guðrún A. Jónsdóttir's profile →
Citations per field
00.5×1.5×
Guðrún A. Jónsdóttir · 1×
Citations per year

Countries citing papers authored by Jeff Nie

Since Specialization
Citations

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

Fields of papers citing papers by Jeff Nie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Jeff Nie, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jeff Nie Line = papers co-authored together Jeff Nie links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 201987
2 201442
3 2013105
4 201338
5 20131
6 201398
7 201287
8 201233
9 201263
10 20123
11 201125
12 2011118
13 2010215
14 2009100
15 200836
16 2008300
17
Induced Pluripotent Stem Cell Lines Derived from Human Somatic Cellsbreakdown →
20077504
18
Whole-Genome Analysis of Histone H3 Lysine 4 and Lysine 27 Methylation in Human Embryonic Stem Cellsbreakdown →
2007544
19 200416
20 200425

About Jeff Nie

Jeff Nie is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging, Immunology and Allergy, Ecology and Genetics, having authored 20 papers that have together received 9.4k indexed citations. Recurring topics across this work include Advanced biosensing and bioanalysis techniques (8 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Pluripotent Stem Cells Research (4 papers), RNA Interference and Gene Delivery (3 papers), Bioinformatics and Genomic Networks (3 papers), Advanced Biosensing Techniques and Applications (3 papers), CRISPR and Genetic Engineering (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Molecular Biology (8.3k citations), Developmental Neuroscience (389 citations), Genetics (810 citations), Aging (110 citations) and Cellular and Molecular Neuroscience (772 citations). Jeff Nie has collaborated with scholars based in United States, China and France. Frequent co-authors include James A. Thomson, Ron Stewart, Shulan Tian, Victor Ruotti, Guðrún A. Jónsdóttir, Igor I. Slukvin, Maxim A. Vodyanik, Junying Yu, Jessica Antosiewicz‐Bourget and Kim Smuga-Otto. Their work appears in journals such as Proceedings of the National Academy of Sciences, Analytical Chemistry, Genome Research, PLoS ONE and Stem Cells.

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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