Peter Langfelder

41.2k total citations · 8 hit papers
45 papers, 24.4k citations indexed

About

Peter Langfelder is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Neurology. According to data from OpenAlex, Peter Langfelder has authored 45 papers receiving a total of 24.4k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 6 papers in Neurology. Recurrent topics in Peter Langfelder's work include Bioinformatics and Genomic Networks (17 papers), Gene expression and cancer classification (12 papers) and Genetic Neurodegenerative Diseases (6 papers). Peter Langfelder is often cited by papers focused on Bioinformatics and Genomic Networks (17 papers), Gene expression and cancer classification (12 papers) and Genetic Neurodegenerative Diseases (6 papers). Peter Langfelder collaborates with scholars based in United States, Netherlands and Canada. Peter Langfelder's co-authors include Steve Horvath, Bin Zhang, Michael C. Oldham, Rui Luo, Song Lin, Daniel H. Geschwind, Roel A. Ophoff, Kazuya Iwamoto, Tadafumi Kato and Geneviève Konopka and has published in prestigious journals such as Cell, The Journal of Chemical Physics and Neuron.

In The Last Decade

Peter Langfelder

45 papers receiving 24.2k citations

Hit Papers

WGCNA: an R package for weighted correlation network anal... 2007 2026 2013 2019 2008 2007 2012 2012 2011 5.0k 10.0k 15.0k
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.

  1. WGCNA: an R package for weighted correlation network analysis
    2008 16.6k citations Peter Langfelder, Steve Horvath BMC Bioinformatics profile →
  2. Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R
    2007 1.3k citations Peter Langfelder, Steve Horvath et al. profile →
  3. FastRFunctions for Robust Correlations and Hierarchical Clustering
    2012 772 citations Peter Langfelder, Steve Horvath profile →
  4. Fast R Functions for Robust Correlations and Hierarchical Clustering.
    2012 679 citations Peter Langfelder, Steve Horvath profile →
  5. Is My Network Module Preserved and Reproducible?
    2011 657 citations Peter Langfelder, Rui Luo et al. PLoS Computational Biology profile →
  6. Eigengene networks for studying the relationships between co-expression modules
    2007 615 citations Peter Langfelder, Steve Horvath BMC Systems Biology profile →
  7. Functional organization of the transcriptome in human brain
    2008 547 citations Michael C. Oldham, Geneviève Konopka et al. Nature Neuroscience profile →
  8. Aging effects on DNA methylation modules in human brain and blood tissue
    2012 469 citations Steve Horvath, Peter Langfelder et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Langfelder United States 29 14.1k 3.8k 3.5k 3.1k 2.9k 45 24.4k
Hidemasa Bono Japan 30 19.5k 1.4× 3.7k 1.0× 3.4k 1.0× 2.1k 0.7× 3.0k 1.0× 108 28.8k
Wataru Fujibuchi Japan 25 18.4k 1.3× 3.7k 1.0× 2.9k 0.8× 2.1k 0.7× 2.6k 0.9× 69 27.4k
Stefan Wyder Switzerland 18 15.6k 1.1× 4.2k 1.1× 2.1k 0.6× 3.3k 1.1× 2.3k 0.8× 26 25.5k
Miho Furumichi Japan 10 16.8k 1.2× 3.4k 0.9× 2.7k 0.8× 2.0k 0.7× 2.3k 0.8× 11 26.0k
Alexander Röth Germany 31 15.5k 1.1× 3.4k 0.9× 1.8k 0.5× 2.5k 0.8× 2.3k 0.8× 80 24.7k
Nada Amin United States 13 21.8k 1.5× 5.5k 1.5× 4.5k 1.3× 2.9k 0.9× 2.9k 1.0× 31 35.2k
Jaime Huerta‐Cepas Spain 35 19.3k 1.4× 3.3k 0.9× 3.8k 1.1× 2.6k 0.9× 3.1k 1.1× 59 30.8k
Allan Peter Davis United States 32 25.8k 1.8× 3.7k 1.0× 3.5k 1.0× 1.8k 0.6× 4.4k 1.5× 55 36.5k
John Quackenbush United States 75 13.9k 1.0× 3.3k 0.9× 2.8k 0.8× 3.6k 1.2× 2.9k 1.0× 293 29.2k
Yoko Sato Japan 31 19.1k 1.3× 3.4k 0.9× 4.0k 1.2× 2.1k 0.7× 2.8k 1.0× 137 30.8k

Countries citing papers authored by Peter Langfelder

Since Specialization
Citations

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

Fields of papers citing papers by Peter Langfelder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter Langfelder

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Langfelder. A scholar is included among the top collaborators of Peter Langfelder 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 Peter Langfelder. Peter Langfelder 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.
Wang, Nan, Shasha Zhang, Peter Langfelder, et al.. (2025). Distinct mismatch-repair complex genes set neuronal CAG-repeat expansion rate to drive selective pathogenesis in HD mice. Cell. 188(6). 1524–1544.e22. 10 indexed citations
2.
3.
Breen, Elizabeth C., Mary E. Sehl, Roger Shih, et al.. (2022). Accelerated aging with HIV occurs at the time of initial HIV infection. iScience. 25(7). 104488–104488. 38 indexed citations
4.
Esmaili, Saeed, Peter Langfelder, T. Grant Belgard, et al.. (2021). Core liver homeostatic co-expression networks are preserved but respond to perturbations in an organism- and disease-specific manner. Cell Systems. 12(5). 432–445.e7. 9 indexed citations
5.
Wang, Nan, Koning Shen, Peter Langfelder, et al.. (2020). Disease-related Huntingtin seeding activities in cerebrospinal fluids of Huntington’s disease patients. Scientific Reports. 10(1). 20295–20295. 13 indexed citations
6.
Quach, Austin, Steve Horvath, Dimitrios N. Vatakis, et al.. (2018). No reliable gene expression biomarkers of current or impending neurocognitive impairment in peripheral blood monocytes of persons living with HIV. Journal of NeuroVirology. 24(3). 350–361. 5 indexed citations
7.
8.
Langfelder, Peter, et al.. (2017). Titanium biomaterials with complex surfaces induced aberrant peripheral circadian rhythms in bone marrow mesenchymal stromal cells. PLoS ONE. 12(8). e0183359–e0183359. 18 indexed citations
9.
Levine, Morgan E., Peter Langfelder, & Steve Horvath. (2017). A Weighted SNP Correlation Network Method for Estimating Polygenic Risk Scores. Methods in molecular biology. 1613. 277–290. 13 indexed citations
10.
Rañola, John Michael O., Peter Langfelder, Kenneth Lange, & Steve Horvath. (2013). Cluster and propensity based approximation of a network. BMC Systems Biology. 7(1). 21–21. 5 indexed citations
11.
Langfelder, Peter, Paul S. Mischel, & Steve Horvath. (2013). When Is Hub Gene Selection Better than Standard Meta-Analysis?. PLoS ONE. 8(4). e61505–e61505. 215 indexed citations
12.
Eijk, Kristel R. van, Simone de Jong, Marco P. Boks, et al.. (2012). Genetic analysis of DNA methylation and gene expression levels in whole blood of healthy human subjects. BMC Genomics. 13(1). 636–636. 162 indexed citations
13.
Park, Christopher C, Greg D. Gale, Simone de Jong, et al.. (2011). Gene networks associated with conditional fear in mice identified using a systems genetics approach. BMC Systems Biology. 5(1). 43–43. 62 indexed citations
14.
Miller, Jeremy A., Chaochao Cai, Peter Langfelder, et al.. (2011). Strategies for aggregating gene expression data: The collapseRows R function. BMC Bioinformatics. 12(1). 322–322. 223 indexed citations
15.
Langfelder, Peter, Rui Luo, Michael C. Oldham, & Steve Horvath. (2011). Is My Network Module Preserved and Reproducible?. PLoS Computational Biology. 7(1). e1001057–e1001057. 657 indexed citations breakdown →
16.
Dewey, Frederick E., Marco Pérez, Matthew T. Wheeler, et al.. (2010). Gene Coexpression Network Topology of Cardiac Development, Hypertrophy, and Failure. Circulation Cardiovascular Genetics. 4(1). 26–35. 71 indexed citations
17.
Mumford, Jeanette A., Steve Horvath, Michael C. Oldham, et al.. (2010). Detecting network modules in fMRI time series: A weighted network analysis approach. NeuroImage. 52(4). 1465–1476. 60 indexed citations
18.
Langfelder, Peter & Steve Horvath. (2008). WGCNA: an R package for weighted correlation network analysis. BMC Bioinformatics. 9(1). 559–559. 16624 indexed citations breakdown →
19.
Oldham, Michael C., Geneviève Konopka, Kazuya Iwamoto, et al.. (2008). Functional organization of the transcriptome in human brain. Nature Neuroscience. 11(11). 1271–1282. 547 indexed citations breakdown →
20.
Langfelder, Peter & Steve Horvath. (2007). Eigengene networks for studying the relationships between co-expression modules. BMC Systems Biology. 1(1). 54–54. 615 indexed citations breakdown →

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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