Adam Sciambi

1.1k total citations
23 papers, 777 citations indexed

About

Adam Sciambi is a scholar working on Molecular Biology, Cancer Research and Biomedical Engineering. According to data from OpenAlex, Adam Sciambi has authored 23 papers receiving a total of 777 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Cancer Research and 9 papers in Biomedical Engineering. Recurrent topics in Adam Sciambi's work include Single-cell and spatial transcriptomics (10 papers), Cancer Genomics and Diagnostics (9 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (8 papers). Adam Sciambi is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), Cancer Genomics and Diagnostics (9 papers) and Innovative Microfluidic and Catalytic Techniques Innovation (8 papers). Adam Sciambi collaborates with scholars based in United States, Sweden and Switzerland. Adam Sciambi's co-authors include Adam R. Abate, Dennis J. Eastburn, Maurizio Pellegrino, Jennifer A. Geis, William M. Oldham, P. Andrew Futreal, Koichi Takahashi, Jairo Matthews, Robert Durruthy-Durruthy and Jose Jacob and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and Blood.

In The Last Decade

Adam Sciambi

20 papers receiving 758 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Adam Sciambi United States 12 516 326 268 115 66 23 777
Robert Kimmerling United States 13 332 0.6× 279 0.9× 125 0.5× 69 0.6× 19 0.3× 14 695
Lih Feng Cheow Singapore 18 598 1.2× 512 1.6× 218 0.8× 84 0.7× 7 0.1× 43 1.1k
Curtis Hughesman Canada 10 237 0.5× 213 0.7× 53 0.2× 98 0.9× 13 0.2× 22 481
Karin Felderer Germany 6 169 0.3× 454 1.4× 68 0.3× 100 0.9× 10 0.2× 8 685
Gregor Kijanka Ireland 18 425 0.8× 315 1.0× 137 0.5× 44 0.4× 8 0.1× 34 850
Daniel Klaue Germany 8 446 0.9× 377 1.2× 53 0.2× 22 0.2× 22 0.3× 11 937
Sora Kim United States 14 102 0.2× 222 0.7× 277 1.0× 85 0.7× 76 1.2× 35 666
Yongjian Yue China 8 130 0.3× 457 1.4× 56 0.2× 52 0.5× 16 0.2× 14 677
Smiti Bhattacharya United States 6 202 0.4× 156 0.5× 48 0.2× 40 0.3× 17 0.3× 8 414

Countries citing papers authored by Adam Sciambi

Since Specialization
Citations

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

Fields of papers citing papers by Adam Sciambi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Adam Sciambi

This figure shows the co-authorship network connecting the top 25 collaborators of Adam Sciambi. A scholar is included among the top collaborators of Adam Sciambi 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 Adam Sciambi. Adam Sciambi 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.
Sciambi, Adam, Daniel Mendoza, Kathryn Thompson, et al.. (2024). Single-Cell Multi-Omic Analysis of AML MRD Reveals Differences in Clonal Architecture between Relapse and Non-Relapse Cases. Blood. 144(Supplement 1). 1568–1568.
2.
Thompson, Kathryn, Benjamin S. Geller, Indira Krishnan, et al.. (2024). A Multiomic, Single-Cell Measurable Residual Disease (scMRD) Assay for Simultaneous Assessment of DNA Mutations and Surface Immunophenotypes in Acute Myeloid Leukemia. Blood. 144(Supplement 1). 6168–6168.
3.
Chowdhury, Onima, Ivan Krešimir Lukić, Adam Sciambi, et al.. (2024). Single-Cell Multiomic Profiling of TP53 Mutated Myelodysplastic Neoplasms - All Clones Are Not Equal. Blood. 144(Supplement 1). 3615–3615. 1 indexed citations
4.
Robinson, Troy M., Robert L. Bowman, Ying Liu, et al.. (2023). Single-cell genotypic and phenotypic analysis of measurable residual disease in acute myeloid leukemia. Science Advances. 9(38). eadg0488–eadg0488. 24 indexed citations
5.
Ooi, Aik T., Dalia Dhingra, Adam Sciambi, et al.. (2021). Abstract 2259: Single-cell multi-omics analysis of SNV, CNV, and protein expression. Cancer Research. 81(13_Supplement). 2259–2259. 1 indexed citations
6.
Pellegrino, Maurizio, Adam Sciambi, Sebastian Treusch, et al.. (2018). High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics. Genome Research. 28(9). 1345–1352. 148 indexed citations
7.
Eastburn, Dennis J., Maurizio Pellegrino, Adam Sciambi, et al.. (2018). Abstract 5348: Single-cell analysis of mutational heterogeneity in acute myeloid leukemia tumors with high-throughput droplet microfluidics. Cancer Research. 78(13_Supplement). 5348–5348. 4 indexed citations
8.
Huang, Phillips, Eve Kandyba, Arnaud Jabouille, et al.. (2017). Lgr6 is a stem cell marker in mouse skin squamous cell carcinoma. Nature Genetics. 49(11). 1624–1632. 46 indexed citations
9.
Pellegrino, Maurizio, et al.. (2016). RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures. BMC Genomics. 17(1). 361–361. 18 indexed citations
10.
Eastburn, Dennis J., Yong Huang, Maurizio Pellegrino, et al.. (2015). Microfluidic droplet enrichment for targeted sequencing. Nucleic Acids Research. 43(13). e86–e86. 34 indexed citations
11.
O’Donovan, Brian D., Tuan M. Tran, Adam Sciambi, & Adam R. Abate. (2014). Picoinjection of Microfluidic Drops Without Metal Electrodes. Journal of Visualized Experiments. 2 indexed citations
12.
Sciambi, Adam & Adam R. Abate. (2014). Generating electric fields in PDMS microfluidic devices with salt water electrodes. Lab on a Chip. 14(15). 2605–2609. 75 indexed citations
13.
Eastburn, Dennis J., Adam Sciambi, & Adam R. Abate. (2014). Identification and genetic analysis of cancer cells with PCR-activated cell sorting. Nucleic Acids Research. 42(16). e128–e128. 54 indexed citations
14.
Pelliccione, Matthew, et al.. (2014). Local imaging of high mobility two-dimensional electron systems with virtual scanning tunneling microscopy. Applied Physics Letters. 105(18). 2 indexed citations
15.
Sciambi, Adam & Adam R. Abate. (2014). Accurate microfluidic sorting of droplets at 30 kHz. Lab on a Chip. 15(1). 47–51. 165 indexed citations
16.
Eastburn, Dennis J., Adam Sciambi, & Adam R. Abate. (2013). Picoinjection Enables Digital Detection of RNA with Droplet RT-PCR. PLoS ONE. 8(4). e62961–e62961. 58 indexed citations
17.
Sciambi, Adam & Adam R. Abate. (2013). Adding reagent to droplets with controlled rupture of encapsulated double emulsions. Biomicrofluidics. 7(4). 44112–44112. 14 indexed citations
18.
Eastburn, Dennis J., Adam Sciambi, & Adam R. Abate. (2013). Ultrahigh-Throughput Mammalian Single-Cell Reverse-Transcriptase Polymerase Chain Reaction in Microfluidic Drops. Analytical Chemistry. 85(16). 8016–8021. 106 indexed citations
19.
Pelliccione, Matthew, et al.. (2012). Design of a scanning gate microscope in a cryogen-free dilution refrigerator. arXiv (Cornell University). 2011. 1 indexed citations
20.
Sciambi, Adam, Matthew Pelliccione, M. P. Lilly, et al.. (2011). Vertical field-effect transistor based on wave-function extension. Physical Review B. 84(8). 20 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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