Will Macnair

2.0k total citations
9 papers, 223 citations indexed

About

Will Macnair is a scholar working on Molecular Biology, Developmental Neuroscience and Genetics. According to data from OpenAlex, Will Macnair has authored 9 papers receiving a total of 223 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Developmental Neuroscience and 1 paper in Genetics. Recurrent topics in Will Macnair's work include Single-cell and spatial transcriptomics (6 papers), Gene Regulatory Network Analysis (4 papers) and Genetic Syndromes and Imprinting (1 paper). Will Macnair is often cited by papers focused on Single-cell and spatial transcriptomics (6 papers), Gene Regulatory Network Analysis (4 papers) and Genetic Syndromes and Imprinting (1 paper). Will Macnair collaborates with scholars based in Switzerland, Netherlands and United Kingdom. Will Macnair's co-authors include Julien Bryois, Manfred Claassen, Paul J. Lucassen, Erik Nutma, Manuel Marzin, Evgenia Salta, Victor A. Iglesias, Suresh Selvaraj, Anna Williams and Carlos P. Fitzsimons and has published in prestigious journals such as Neuron, Nature Neuroscience and Bioinformatics.

In The Last Decade

Will Macnair

9 papers receiving 223 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Will Macnair Switzerland	6	133	52	39	34	24	9	223
Wenyu Ding China	5	194 1.5×	61 1.2×	60 1.5×	48 1.4×	28 1.2×	6	275
Vilma Rraklli Sweden	9	226 1.7×	48 0.9×	16 0.4×	34 1.0×	55 2.3×	11	320
Emily A. Meyers United States	6	183 1.4×	31 0.6×	85 2.2×	39 1.1×	18 0.8×	10	297
Ryan A. Gallo United States	9	149 1.1×	93 1.8×	28 0.7×	14 0.4×	9 0.4×	34	278
Fatih Semerci United States	7	131 1.0×	21 0.4×	66 1.7×	28 0.8×	32 1.3×	10	226
Vukasin M. Jovanovic United States	8	184 1.4×	29 0.6×	35 0.9×	10 0.3×	15 0.6×	13	274
Julian Curiel United States	7	202 1.5×	34 0.7×	24 0.6×	51 1.5×	10 0.4×	9	305
Nathalie Escande‐Beillard Singapore	10	130 1.0×	37 0.7×	26 0.7×	49 1.4×	62 2.6×	16	272
Nicola Micali United States	10	277 2.1×	42 0.8×	87 2.2×	22 0.6×	37 1.5×	11	380
Léna Guillot‐Noël France	8	134 1.0×	39 0.8×	30 0.8×	74 2.2×	9 0.4×	10	325

Countries citing papers authored by Will Macnair

Since Specialization

Citations

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

Fields of papers citing papers by Will Macnair

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Will Macnair

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

All Works

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9 of 9 papers shown

Lange, Simona, Martin Ebeling, Will Macnair, et al.. (2024). Fenebrutinib, a Bruton’s tyrosine kinase inhibitor, blocks distinct human microglial signaling pathways. Journal of Neuroinflammation. 21(1). 276–276. 5 indexed citations

Macnair, Will & Mark D. Robinson. (2023). SampleQC: robust multivariate, multi-cell type, multi-sample quality control for single-cell data. Genome biology. 24(1). 23–23. 6 indexed citations

Bryois, Julien, et al.. (2023). Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: Reconciling controversy or fueling the debate?. Neuron. 111(11). 1714–1731.e3. 47 indexed citations

Bryois, Julien, Daniela Calini, Will Macnair, et al.. (2022). Cell-type-specific cis-eQTLs in eight human brain cell types identify novel risk genes for psychiatric and neurological disorders. Nature Neuroscience. 25(8). 1104–1112. 106 indexed citations

Macnair, Will, Revant Gupta, & Manfred Claassen. (2022). psupertime: supervised pseudotime analysis for time-series single-cell RNA-seq data. Bioinformatics. 38(Supplement_1). i290–i298. 16 indexed citations

Taylor‐King, Jake P., Asbjørn Nilsen Riseth, Will Macnair, & Manfred Claassen. (2020). Dynamic distribution decomposition for single-cell snapshot time series identifies subpopulations and trajectories during iPSC reprogramming. PLoS Computational Biology. 16(1). e1007491–e1007491. 2 indexed citations

Wirsching, Hans‐Georg, Manuela Silginer, Will Macnair, et al.. (2020). Negative allosteric modulators of metabotropic glutamate receptor 3 target the stem-like phenotype of glioblastoma. Molecular Therapy — Oncolytics. 20. 166–174. 5 indexed citations

Macnair, Will, et al.. (2019). Tree‐ensemble analysis assesses presence of multifurcations in single cell data. Molecular Systems Biology. 15(3). e8552–e8552. 4 indexed citations

Weller, Michael, Will Macnair, Katja Eschbach, et al.. (2017). TGF-β induces oncofetal fibronectin that, in turn, modulates TGF-β superfamily signaling in endothelial cells. Journal of Cell Science. 131(1). 32 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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