Jesse Gillis

10.0k total citations
72 papers, 3.1k citations indexed

About

Jesse Gillis is a scholar working on Molecular Biology, Cognitive Neuroscience and Genetics. According to data from OpenAlex, Jesse Gillis has authored 72 papers receiving a total of 3.1k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 11 papers in Cognitive Neuroscience and 10 papers in Genetics. Recurrent topics in Jesse Gillis's work include Single-cell and spatial transcriptomics (27 papers), Bioinformatics and Genomic Networks (25 papers) and Gene expression and cancer classification (18 papers). Jesse Gillis is often cited by papers focused on Single-cell and spatial transcriptomics (27 papers), Bioinformatics and Genomic Networks (25 papers) and Gene expression and cancer classification (18 papers). Jesse Gillis collaborates with scholars based in United States, Canada and France. Jesse Gillis's co-authors include Paul Pavlidis, Sara Ballouz, Megan Crow, Anirban Paul, Meeta Mistry, Z. Josh Huang, Alexander Dobin, Stephan Fischer, Ricardo Raudales and Miao He and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jesse Gillis

70 papers receiving 3.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jesse Gillis United States 30 2.2k 578 446 417 301 72 3.1k
Erika Sasaki Japan 32 2.2k 1.0× 653 1.1× 457 1.0× 421 1.0× 275 0.9× 175 4.0k
Caleb Webber United Kingdom 28 1.7k 0.8× 1.2k 2.1× 377 0.8× 311 0.7× 324 1.1× 58 3.0k
Dietrich Stephan United States 32 2.3k 1.0× 812 1.4× 520 1.2× 371 0.9× 253 0.8× 78 3.9k
Apuã C.M. Paquola United States 18 1.6k 0.7× 298 0.5× 375 0.8× 128 0.3× 240 0.8× 27 2.0k
Harrison W. Gabel United States 23 2.2k 1.0× 1.1k 1.8× 397 0.9× 416 1.0× 200 0.7× 36 2.9k
Atsushi Yoshiki Japan 35 2.2k 1.0× 839 1.5× 987 2.2× 434 1.0× 187 0.6× 108 4.2k
Chongyuan Luo United States 19 3.1k 1.4× 732 1.3× 232 0.5× 134 0.3× 913 3.0× 33 4.1k
Geneviève Konopka United States 41 3.2k 1.4× 1.2k 2.1× 574 1.3× 778 1.9× 159 0.5× 99 5.6k
Gabriel Santpere Spain 25 1.3k 0.6× 302 0.5× 402 0.9× 186 0.4× 111 0.4× 51 2.6k
Irina Voineagu Australia 18 2.3k 1.0× 1.3k 2.3× 440 1.0× 994 2.4× 158 0.5× 34 3.3k

Countries citing papers authored by Jesse Gillis

Since Specialization
Citations

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

Fields of papers citing papers by Jesse Gillis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jesse Gillis

This figure shows the co-authorship network connecting the top 25 collaborators of Jesse Gillis. A scholar is included among the top collaborators of Jesse Gillis 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 Jesse Gillis. Jesse Gillis 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.
Gillis, Jesse, et al.. (2024). Coexpression enhances cross-species integration of single-cell RNA sequencing across diverse plant species. Nature Plants. 10(7). 1075–1080. 3 indexed citations
2.
Fischer, Stephan & Jesse Gillis. (2022). Defining the extent of gene function using ROC curvature. Bioinformatics. 38(24). 5390–5397. 2 indexed citations
3.
Kawaguchi, Risa Karakida, et al.. (2022). Learning single-cell chromatin accessibility profiles using meta-analytic marker genes. Briefings in Bioinformatics. 24(1). 2 indexed citations
4.
Fox, Nathan A., et al.. (2022). A global high-density chromatin interaction network reveals functional long-range and trans-chromosomal relationships. Genome biology. 23(1). 238–238. 6 indexed citations
5.
Kaminow, Benjamin, Sara Ballouz, Jesse Gillis, & Alexander Dobin. (2022). Pan-human consensus genome significantly improves the accuracy of RNA-seq analyses. Genome Research. 32(4). 738–749. 8 indexed citations
6.
Sun, Yu-Chi, Xiaoyin Chen, Stephan Fischer, et al.. (2021). Integrating barcoded neuroanatomy with spatial transcriptional profiling enables identification of gene correlates of projections. Nature Neuroscience. 24(6). 873–885. 59 indexed citations
7.
Ortiz, Cantin, Daniel Fürth, Stephan Fischer, et al.. (2021). Assessing the replicability of spatial gene expression using atlas data from the adult mouse brain. PLoS Biology. 19(7). e3001341–e3001341. 6 indexed citations
8.
Harris, Benjamin, Megan Crow, Stephan Fischer, & Jesse Gillis. (2021). Single-cell co-expression analysis reveals that transcriptional modules are shared across cell types in the brain. Cell Systems. 12(7). 748–756.e3. 17 indexed citations
9.
Lee, J. Jack, et al.. (2020). CoCoCoNet: conserved and comparative co-expression across a diverse set of species. Nucleic Acids Research. 48(W1). W566–W571. 28 indexed citations
10.
Pang, Chi Nam Ignatius, Sara Ballouz, L Thibaut, et al.. (2020). Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes. Molecular & Cellular Proteomics. 19(11). 1876–1895. 15 indexed citations
11.
Ballouz, Sara, Alexander Dobin, & Jesse Gillis. (2019). Is it time to change the reference genome?. Genome biology. 20(1). 159–159. 110 indexed citations
12.
Chen, Xiaoyin, Yu-Chi Sun, Huiqing Zhan, et al.. (2019). High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing. Cell. 179(3). 772–786.e19. 139 indexed citations
13.
Li, Siran, Jude Kendall, Sarah Park, et al.. (2019). Copolymerization of single-cell nucleic acids into balls of acrylamide gel. Genome Research. 30(1). 49–61. 6 indexed citations
14.
Crow, Megan, Anirban Paul, Sara Ballouz, Zhi Huang, & Jesse Gillis. (2018). Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor. Nature Communications. 9(1). 884–884. 165 indexed citations
15.
Ballouz, Sara & Jesse Gillis. (2017). Strength of functional signature correlates with effect size in autism. Genome Medicine. 9(1). 64–64. 7 indexed citations
16.
Ballouz, Sara, Melanie Weber, Paul Pavlidis, & Jesse Gillis. (2016). EGAD: ultra-fast functional analysis of gene networks. Bioinformatics. 33(4). 612–614. 54 indexed citations
17.
Gillis, Jesse, Sara Ballouz, & Paul Pavlidis. (2014). Bias tradeoffs in the creation and analysis of protein–protein interaction networks. Journal of Proteomics. 100. 44–54. 48 indexed citations
18.
Mazurek, Anthony, Youngkyu Park, Cornelius Miething, et al.. (2014). Acquired Dependence of Acute Myeloid Leukemia on the DEAD-Box RNA Helicase DDX5. Cell Reports. 7(6). 1887–1899. 31 indexed citations
19.
Wu, Chenggang, et al.. (2009). Repeated hypoxic episodes induce seizures and alter hippocampal network activities in mice. Neuroscience. 161(2). 599–613. 15 indexed citations
20.
Wu, Chenggang, et al.. (2006). Spontaneous rhythmic field potentials of isolated mouse hippocampal–subicular–entorhinal cortices in vitro. The Journal of Physiology. 576(2). 457–476. 28 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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