Maja Jankovic

930 total citations · 1 hit paper
8 papers, 574 citations indexed

About

Maja Jankovic is a scholar working on Molecular Biology, Hematology and Immunology. According to data from OpenAlex, Maja Jankovic has authored 8 papers receiving a total of 574 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Hematology and 2 papers in Immunology. Recurrent topics in Maja Jankovic's work include CRISPR and Genetic Engineering (3 papers), Acute Myeloid Leukemia Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Maja Jankovic is often cited by papers focused on CRISPR and Genetic Engineering (3 papers), Acute Myeloid Leukemia Research (2 papers) and Single-cell and spatial transcriptomics (2 papers). Maja Jankovic collaborates with scholars based in United States, Canada and Germany. Maja Jankovic's co-authors include Alejo Rodriguez-Fraticelli, Caleb Weinreb, Fernando D. Camargo, Allon M. Klein, Samuel L. Wolock, Sachin Patel, Jianlong Sun, Raffaele Calogero, Riccardo Panero and Sally Lowell and has published in prestigious journals such as Nature, Molecular Cancer Therapeutics and ACS Chemical Biology.

In The Last Decade

Maja Jankovic

8 papers receiving 570 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.

Clonal analysis of lineage fate in native haematopoiesis

2018 391 citations Alejo Rodriguez-Fraticelli, Samuel L. Wolock et al. Nature profile →

Peers

Maja Jankovic

MB

HEMAT

IMMUN

CR

GENET

Christopher Day Canada

Keegan Rowe Canada

Karina Eiwen Germany

Shabnam Kharazi Sweden

Elaine Ma United States

Caroline A. Oedekoven United Kingdom

Mikkel Bruhn Schuster Denmark

Florian Grünschläger Germany

Jenny Klintman Sweden

Azusa Matsubara Japan

Christopher Day Canada

Maja Jankovic

292 ×0.9

MB

240 ×0.8

HEMAT

181 ×0.8

IMMUN

79 ×1.1

CR

56 ×0.8

GENET

Citations per year, relative to Maja Jankovic Maja Jankovic (= 1×) peers Christopher Day

Countries citing papers authored by Maja Jankovic

Since Specialization

Citations

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

Fields of papers citing papers by Maja Jankovic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maja Jankovic

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

All Works

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8 of 8 papers shown

1.

Jankovic, Maja, Gabriela Galicia-Vázquez, Yi Ding, et al.. (2024). The E3 ubiquitin ligase Herc1 modulates the response to nucleoside analogs in acute myeloid leukemia. Blood Advances. 8(20). 5315–5329. 1 indexed citations

2.

Mercier, François, Jiantao Shi, David B. Sykes, et al.. (2022). In vivo genome-wide CRISPR screening in murine acute myeloid leukemia uncovers microenvironmental dependencies. Blood Advances. 6(17). 5072–5084. 11 indexed citations

3.

Long, Jason E., Maja Jankovic, & Danilo Maddalo. (2021). Drug Discovery Oncology in a Mouse: concepts, Models and Limitations. Future Science OA. 7(8). FSO737–FSO737. 5 indexed citations

4.

Abusarah, Jamilah, Nehmé El-Hachem, Abed El-Hakim El-Kadiry, et al.. (2020). TACIMA-218: A Novel Pro-Oxidant Agent Exhibiting Selective Antitumoral Activity. Molecular Cancer Therapeutics. 20(1). 37–49. 4 indexed citations

5.

Rodriguez-Fraticelli, Alejo, Caleb Weinreb, Shou‐Wen Wang, et al.. (2020). Single-cell lineage tracing unveils a role for TCF15 in haematopoiesis. Nature. 583(7817). 585–589. 143 indexed citations

6.

Kim, Hyun-Hee, et al.. (2020). Yeast Tripartite Biosensors Sensitive to Protein Stability and Aggregation Propensity. ACS Chemical Biology. 15(4). 1078–1088. 4 indexed citations

7.

Rodriguez-Fraticelli, Alejo, Samuel L. Wolock, Caleb Weinreb, et al.. (2018). Clonal analysis of lineage fate in native haematopoiesis. Nature. 553(7687). 212–216. 391 indexed citations breakdown →

8.

Jankovic, Maja, et al.. (2015). The Surgical Lips Deformity Corrected with Hyaluronic Fillers: A Case Report. Open Access Macedonian Journal of Medical Sciences. 3(3). 423–425. 15 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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