Sascha Abramson

694 citations
22 papers · 267 · h-index 8

Impact in

Papers in

    • CAR-T cell therapy research 11
    • Immune cells in cancer 7
    • Phagocytosis and Immune Regulation 5
    • Immunotherapy and Immune Responses 4

Sascha Abramson

22 papers receiving 260 citations

Peers

Sascha Abramson
Comparison fields: 5 of 75
  • Immunology 52
  • Biomaterials 30
  • Surfaces, Coatings and Films 16
  • Oncology 53
  • Rehabilitation 12
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Citations per field
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Citations per year

Countries citing papers authored by Sascha Abramson

Since Specialization
Citations

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

Fields of papers citing papers by Sascha Abramson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Sascha Abramson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sascha Abramson Line = papers co-authored together Sascha Abramson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200457
2 200442
3 200538
4
The Mechanism of Cell Interaction and Response on Decellularized Human Amniotic Membrane: Implications in Wound Healing.
200723
5 202122
6 201522
7 202111
8 202110
9 20046
10 20225
11 20224
12 20214
13 20214
14 20224
15 20213
16 20223
17 20032
18 20232
19
Placenta Derived Adherent Cell (PDAC) Interaction and Response on Extracellular Matrix Isolated from Human Placenta t.
20082
20
USING LOGICAL ANALYSIS OF DATA (LAD) TO FIND PHYSIO-MECHANICAL DATA PATTERNS WHICH PREDICT CELLULAR OUTCOMES
20021

About Sascha Abramson

Sascha Abramson is a scholar working on Oncology, Immunology, Molecular Biology, Computational Theory and Mathematics and Materials Chemistry, having authored 22 papers that have together received 267 indexed citations. Recurring topics across this work include CAR-T cell therapy research (11 papers), Immune cells in cancer (7 papers), Phagocytosis and Immune Regulation (5 papers), Immunotherapy and Immune Responses (4 papers), Computational Drug Discovery Methods (3 papers), Machine Learning in Materials Science (3 papers), Neuroblastoma Research and Treatments (2 papers) and Tissue Engineering and Regenerative Medicine (2 papers). The work is most often cited by research in Immunology (52 citations), Biomaterials (30 citations), Surfaces, Coatings and Films (16 citations), Oncology (53 citations) and Rehabilitation (12 citations). Sascha Abramson has collaborated with scholars based in United States and Switzerland. Frequent co-authors include Joachim Kohn, Doyle Knight, Jack R. Smith, Gabriela Alexe, Peter L. Hammer, Norbert Weber, William J. Welsh, Vladyslav Kholodovych, Michael Klichinsky and Thomas Condamine. Their work appears in journals such as Cancer Research, Polymer, Macromolecular Rapid Communications, Journal of Biomedical Materials Research Part A and Journal of Vascular Surgery.

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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