Mateo Sokač

3.3k total citations · 1 hit paper
18 papers, 150 citations indexed

About

Mateo Sokač is a scholar working on Molecular Biology, Immunology and Cancer Research. According to data from OpenAlex, Mateo Sokač has authored 18 papers receiving a total of 150 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 4 papers in Immunology and 4 papers in Cancer Research. Recurrent topics in Mateo Sokač's work include Cancer Genomics and Diagnostics (4 papers), interferon and immune responses (2 papers) and Epigenetics and DNA Methylation (2 papers). Mateo Sokač is often cited by papers focused on Cancer Genomics and Diagnostics (4 papers), interferon and immune responses (2 papers) and Epigenetics and DNA Methylation (2 papers). Mateo Sokač collaborates with scholars based in Denmark, Croatia and United States. Mateo Sokač's co-authors include Nicolai J. Birkbak, Hugo J.W.L. Aerts, Suraj Pai, Simon Bernatz, Ahmed Hosny, Dennis Bontempi, Tafadzwa L. Chaunzwa, Raymond H. Mak, Johanne Ahrenfeldt and Martin R. Jakobsen and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Cancer Research.

In The Last Decade

Mateo Sokač

14 papers receiving 146 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.

Foundation model for cancer imaging biomarkers

2024 63 citations Suraj Pai, Dennis Bontempi et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mateo Sokač Denmark	6	43	40	36	34	28	18	150
Kelly Offermans Netherlands	6	43 1.0×	27 0.7×	42 1.2×	32 0.9×	59 2.1×	14	136
Mehmet A. Baysal United States	5	79 1.8×	31 0.8×	50 1.4×	16 0.5×	45 1.6×	13	208
Josien C.A. Jenniskens Netherlands	6	40 0.9×	26 0.7×	28 0.8×	32 0.9×	40 1.4×	12	136
Fangjin Huang United States	6	26 0.6×	35 0.9×	34 0.9×	31 0.9×	19 0.7×	8	109
Yibo Zhang China	8	55 1.3×	83 2.1×	42 1.2×	47 1.4×	24 0.9×	29	205
Xijing Yan China	6	22 0.5×	89 2.2×	58 1.6×	29 0.9×	39 1.4×	13	215
Manuela Benary Germany	8	32 0.7×	60 1.5×	71 2.0×	75 2.2×	46 1.6×	16	245
Zebin Jiang China	9	44 1.0×	38 0.9×	105 2.9×	41 1.2×	100 3.6×	14	307
Xiaoying Lou China	7	55 1.3×	64 1.6×	8 0.2×	29 0.9×	16 0.6×	13	118

Countries citing papers authored by Mateo Sokač

Since Specialization

Citations

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

Fields of papers citing papers by Mateo Sokač

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mateo Sokač

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

All Works

Sort: Min cites: Since: Top N: Style:

18 of 18 papers shown

Garde, Christian, Sri H. Ramarathinam, Mateo Sokač, et al.. (2025). Endogenous viral elements constitute a complementary source of antigens for personalized cancer vaccines. npj Vaccines. 10(1). 54–54. 2 indexed citations

Brlek, Petar, Leo Mršić, Mateo Sokač, et al.. (2025). Exploring the Pharmacogenomic Map of Croatia: PGx Clustering of 522-Patient Cohort Based on UMAP + HDBSCAN Algorithm. International Journal of Molecular Sciences. 26(2). 589–589.

Sokač, Mateo, et al.. (2025). Automated Grading Through Contrastive Learning: A Gradient Analysis and Feature Ablation Approach. Machine Learning and Knowledge Extraction. 7(2). 41–41.

Pai, Suraj, Dennis Bontempi, Mateo Sokač, et al.. (2024). Foundation model for cancer imaging biomarkers. Nature Machine Intelligence. 6(3). 354–367. 63 indexed citations breakdown →

Puškarić, Staša, Mateo Sokač, Živana Ninčević Gladan, et al.. (2024). Extracted Spectral Signatures from the Water Column as a Tool for the Prediction of the Structure of a Marine Microbial Community. Journal of Marine Science and Engineering. 12(2). 286–286.

Žagar, Martin, et al.. (2024). Study on Collaborative Smart Farming over Digital Platform. 20–24.

Sokač, Mateo, et al.. (2024). Bridging Artificial Intelligence and Neurological Signals (BRAINS): A Novel Framework for Electroencephalogram-Based Image Generation. Information. 15(7). 405–405. 1 indexed citations

Sokač, Mateo, et al.. (2024). Graph Convolutional Networks for Predicting Cancer Outcomes and Stage: A Focus on cGAS-STING Pathway Activation. SHILAP Revista de lepidopterología. 6(3). 2033–2048. 1 indexed citations

Žagar, Martin, et al.. (2024). Data Analytics in Agriculture: Enhancing Decision-Making for Crop Yield Optimization and Sustainable Practices. Sustainability. 16(17). 7331–7331. 5 indexed citations

10.

Ahrenfeldt, Johanne, et al.. (2023). The ratio of adaptive to innate immune cells differs between genders and associates with improved prognosis and response to immunotherapy. PLoS ONE. 18(2). e0281375–e0281375. 5 indexed citations

11.

Sokač, Mateo, et al.. (2023). Spatial transformation of multi-omics data unlocks novel insights into cancer biology. eLife. 12. 9 indexed citations

12.

Sokač, Mateo, et al.. (2023). Spatial transformation of multi-omics data unlocks novel insights into cancer biology. eLife. 12. 2 indexed citations

13.

Sokač, Mateo, Johanne Ahrenfeldt, Kevin Litchfield, et al.. (2022). Classifying cGAS-STING Activity Links Chromosomal Instability with Immunotherapy Response in Metastatic Bladder Cancer. Cancer Research Communications. 2(8). 762–771. 12 indexed citations

14.

Ahrenfeldt, Johanne, Mateo Sokač, Judit Kisistók, et al.. (2022). Treatment Represents a Key Driver of Metastatic Cancer Evolution. Cancer Research. 82(16). 2918–2927. 17 indexed citations

15.

Pedersen, Jesper, Mateo Sokač, Boe Sandahl Sørensen, et al.. (2022). Increased Soluble PD-1 Predicts Response to Nivolumab plus Ipilimumab in Melanoma. Cancers. 14(14). 3342–3342. 18 indexed citations

16.

Ahrenfeldt, Johanne, et al.. (2022). Computational Analysis Reveals the Temporal Acquisition of Pathway Alterations during the Evolution of Cancer. Cancers. 14(23). 5817–5817. 2 indexed citations

17.

Sokač, Mateo, et al.. (2021). Work-in-Progress: Data Science Framework for Environmental Protection Education. Scopus (Elsevier). 4. 1296–1300. 1 indexed citations

18.

Sokač, Mateo, et al.. (2016). UAV application in ecology: Data collecting with quad-copter equipped with Arduino based measurement platform. 233–236. 12 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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