Gal Dinstag

531 citations
13 papers · 65 · h-index 4

Impact in

    • Cancer Genomics and Diagnostics
    • Bioinformatics and Genomic Networks
    • Gene expression and cancer classification
    • Single-cell and spatial transcriptomics

Papers in

    • Cancer Immunotherapy and Biomarkers 2
    • PARP inhibition in cancer therapy 1
    • Cancer Genomics and Diagnostics 5

Gal Dinstag

9 papers receiving 65 citations

Peers

Gal Dinstag
Comparison fields: 5 of 19
  • Cancer Research 20
  • Molecular Biology 35
  • Oncology 12
  • Hepatology 3
  • Computational Theory and Mathematics 6
Replace Mahmoud Charif with:
Mahmoud Charif United States
Sebastian Vaughan United Kingdom
Jule Harbig Germany
Jane Foo Canada
Marc Pollitt United Kingdom
Sukanya Panja United States
Gareth Hughes United Kingdom
Ohtani Shoichiro Japan
Gal Dinstag relative to Mahmoud Charif United States Mahmoud Charif's profile →
Citations per field
00.5×
Mahmoud Charif · 1×
Citations per year

Countries citing papers authored by Gal Dinstag

Since Specialization
Citations

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

Fields of papers citing papers by Gal Dinstag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Gal Dinstag, 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 Gal Dinstag Line = papers co-authored together Gal Dinstag links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 201940
2 202211
3 20195
4 20233
5 20252
6 20231
7 20221
8 20221
9 20231
10 20250
11 20250
12 20250
13 20250

About Gal Dinstag

Gal Dinstag is a scholar working on Oncology, Cancer Research, Molecular Biology, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 13 papers that have together received 65 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (5 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Bioinformatics and Genomic Networks (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), AI in cancer detection (2 papers), Sarcoma Diagnosis and Treatment (1 paper), PARP inhibition in cancer therapy (1 paper) and Ferroptosis and cancer prognosis (1 paper). The work is most often cited by research in Cancer Research (20 citations), Molecular Biology (35 citations), Oncology (12 citations), Hepatology (3 citations) and Computational Theory and Mathematics (6 citations). Gal Dinstag has collaborated with scholars based in Israel, United States and Australia. Frequent co-authors include Ron Shamir, Kenneth Aldape, Tuvik Beker, Eytan Ruppin, Ranit Aharonov, David Amar, Erik Ingelsson, Eyal Schiff, Euan A. Ashley and Razelle Kurzrock. Their work appears in journals such as Journal of Clinical Oncology, Journal for ImmunoTherapy of Cancer, PLoS ONE, Oral Oncology and Bioinformatics.

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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