Thomas D. Sherman

1.4k total citations · 1 hit paper
12 papers, 472 citations indexed

About

Thomas D. Sherman is a scholar working on Molecular Biology, Economics and Econometrics and Biophysics. According to data from OpenAlex, Thomas D. Sherman has authored 12 papers receiving a total of 472 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Economics and Econometrics and 2 papers in Biophysics. Recurrent topics in Thomas D. Sherman's work include Single-cell and spatial transcriptomics (7 papers), Gene expression and cancer classification (3 papers) and RNA modifications and cancer (2 papers). Thomas D. Sherman is often cited by papers focused on Single-cell and spatial transcriptomics (7 papers), Gene expression and cancer classification (3 papers) and RNA modifications and cancer (2 papers). Thomas D. Sherman collaborates with scholars based in United States, Canada and Russia. Thomas D. Sherman's co-authors include Elana J. Fertig, Genevieve Stein-O’Brien, Loyal A. Goff, Seth Blackshaw, Brian S. Clark, Emily F. Davis-Marcisak, Thanh Hoang, Fion Shiau, Richard M. Gronostajski and Clayton P. Santiago and has published in prestigious journals such as Neuron, Bioinformatics and Cancer Research.

In The Last Decade

Thomas D. Sherman

12 papers receiving 468 citations

Hit Papers

align trajectories

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.

Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification

2019 301 citations Brian S. Clark, Genevieve Stein-O’Brien et al. Neuron profile →

Peers

Thomas D. Sherman

MB

CMN

IMMUN

CR

CB

Clayton P. Santiago United States

Thanh Hoang United States

Fion Shiau United States

Dario Bressan United Kingdom

Qi Miao China

Kristin E. Cox United States

Xuejie Yang China

Frédéric Blond France

Evgenya Y. Popova United States

Clayton P. Santiago United States

Thomas D. Sherman

467 ×1.1

MB

84 ×1.4

CMN

52 ×0.9

IMMUN

36 ×0.6

CR

67 ×1.2

CB

Citations per year, relative to Thomas D. Sherman Thomas D. Sherman (= 1×) peers Clayton P. Santiago

Countries citing papers authored by Thomas D. Sherman

Since Specialization

Citations

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

Fields of papers citing papers by Thomas D. Sherman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas D. Sherman. 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 Thomas D. Sherman. The network helps show where Thomas D. Sherman may publish in the future.

Co-authorship network of co-authors of Thomas D. Sherman

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

All Works

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12 of 12 papers shown

1.

Mitchell, Jacob T., Emily F. Davis-Marcisak, Thomas D. Sherman, et al.. (2023). Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS. Nature Protocols. 18(12). 3690–3731. 6 indexed citations

2.

Stein-O’Brien, Genevieve, Brian S. Clark, Thomas D. Sherman, et al.. (2021). Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species. Cell Systems. 12(2). 203–203. 3 indexed citations

3.

Fowler, Mark, et al.. (2021). Quantifying the Impact of the COVID-19 Pandemic on Passenger Vehicle Drivers’ Willingness to Pay for Travel Time Savings and Reliability. Transportation Research Record Journal of the Transportation Research Board. 2677(4). 142–153. 5 indexed citations

4.

Sherman, Thomas D., et al.. (2020). CoGAPS 3: Bayesian non-negative matrix factorization for single-cell analysis with asynchronous updates and sparse data structures. BMC Bioinformatics. 21(1). 453–453. 18 indexed citations

5.

Davis-Marcisak, Emily F., Thomas D. Sherman, Genevieve Stein-O’Brien, et al.. (2019). Differential Variation Analysis Enables Detection of Tumor Heterogeneity Using Single-Cell RNA-Sequencing Data. Cancer Research. 79(19). 5102–5112. 26 indexed citations

6.

Sherman, Thomas D., Luciane T. Kagohara, Raymond Cheng, et al.. (2019). CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer. PLoS Computational Biology. 14(4). e1006935–e1006935. 1 indexed citations

7.

Stein-O’Brien, Genevieve, Brian S. Clark, Thomas D. Sherman, et al.. (2019). Decomposing Cell Identity for Transfer Learning across Cellular Measurements, Platforms, Tissues, and Species. Cell Systems. 8(5). 395–411.e8. 81 indexed citations

8.

Clark, Brian S., Genevieve Stein-O’Brien, Fion Shiau, et al.. (2019). Single-Cell RNA-Seq Analysis of Retinal Development Identifies NFI Factors as Regulating Mitotic Exit and Late-Born Cell Specification. Neuron. 102(6). 1111–1126.e5. 301 indexed citations breakdown →

9.

Kagohara, Luciane T., Michael Considine, Genevieve Stein-O’Brien, et al.. (2019). Abstract 3024: Transcriptional and epigenetic regulation of resistance markers in cetuximab sensitive HNSCC cells. Cancer Research. 79(13_Supplement). 3024–3024. 1 indexed citations

10.

Sherman, Thomas D., Jack Fu, Robert B. Scharpf, Alexandre Bureau, & Ingo Ruczinski. (2018). Detection of rare disease variants in extended pedigrees using RVS. Bioinformatics. 35(14). 2509–2511. 2 indexed citations

11.

Stein-O’Brien, Genevieve, Jacob Carey, Michael Considine, et al.. (2017). PatternMarkers & GWCoGAPS for novel data-driven biomarkers via whole transcriptome NMF. Bioinformatics. 33(12). 1892–1894. 25 indexed citations

12.

Sherman, Thomas D., et al.. (2007). Are Life Settlements a Security?. The journal of structured finance. 12(4). 55–60. 3 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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