Ning Leng

6.4k citations
33 papers · 2.4k indexed · 1 hit paper · h-index 19

Impact in

    • Cancer-related molecular mechanisms research
    • Single-cell and spatial transcriptomics
    • Gene expression and cancer classification
    • Gene Regulatory Network Analysis
    • Pluripotent Stem Cells Research
    • RNA Research and Splicing
    • RNA modifications and cancer
    • Genomics and Phylogenetic Studies

Papers in

Ning Leng

31 papers receiving 2.3k citations

Hit Papers

EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments 2013 · 938 citations
9382013202620172021250500750

Peers

Ning Leng
Comparison fields: 5 of 132
  • Cancer Research 430
  • Molecular Biology 1.7k
  • Biophysics 94
  • Immunology 183
  • Aging 15
Replace San Ming Wang with:
San Ming Wang United States
Shian Su Australia
Hailiang Mei Netherlands
Javier Santoyo‐López Spain
Ian Sudbery United Kingdom
Nuno A. Fonseca Portugal
Itoshi Nikaido Japan
Roland F. Schwarz Germany
Hamed S. Najafabadi Canada
Yangzhou Wang China
Ning Leng relative to San Ming Wang United States San Ming Wang's profile →
Citations per field
00.5×3.9×
San Ming Wang · 1×
Citations per year

Countries citing papers authored by Ning Leng

Since Specialization
Citations

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

Fields of papers citing papers by Ning Leng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ning Leng, 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 Ning Leng Line = papers co-authored together Ning Leng links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1
EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments
Hit paper breakdown →
2013938
2 2016302
3 2017190
4 2015116
5 2017105
6 2013105
7 201489
8 201569
9 201861
10 201355
11 201449
12 201835
13 201533
14 201632
15 201526
16 201825
17 201622
18 202020
19 201419
20 201318

About Ning Leng

Ning Leng is a scholar working on Aging, Cancer Research, Molecular Biology, Statistics and Probability and Modeling and Simulation, having authored 33 papers that have together received 2.4k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (8 papers), Cancer Immunotherapy and Biomarkers (4 papers), Bladder and Urothelial Cancer Treatments (3 papers), Epigenetics and DNA Methylation (3 papers), Ferroptosis and cancer prognosis (3 papers), Cancer-related molecular mechanisms research (3 papers), Molecular Biology Techniques and Applications (3 papers) and CRISPR and Genetic Engineering (3 papers). The work is most often cited by research in Cancer Research (430 citations), Molecular Biology (1.7k citations), Biophysics (94 citations), Immunology (183 citations) and Aging (15 citations). Ning Leng has collaborated with scholars based in United States, France and United Kingdom. Frequent co-authors include Christina Kendziorski, Ron Stewart, James A. Thomson, Anna I. Rissman, Michael N. Gould, Jill D. Haag, Bart M. G. Smits, John A. Dawson, Victor Ruotti and Li‐Fang Chu. Their work appears in journals such as Bioinformatics, Nature Methods, Nature Communications, Journal of Clinical Oncology and PLoS Computational Biology.

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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